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The future increase of chronic diseases in the world requires new challenges in the health domain to improve patients' care from the point of view of the organizational processes, clinical pathways and technological solutions of digital health. For this reason, the present paper aims to focus on the study and application of well-known clinical practices and efficient organizational approaches through an innovative model (TALIsMAn) to support new care process redesign and digitalization for chronic patients.

In addition to specific clinical models employed to manage chronic conditions such as the Population Health Management and Chronic Care Model, we introduce a Business Process Management methodology implementation supported by a set of e-health technologies, in order to manage Care Pathways (CPs) digitalization and procedures improvement.

This study shows that telemedicine services with advanced devices and technologies are not enough to provide significant changes in the healthcare sector if other key aspects such as health processes, organizational systems, interactions between actors and responsibilities are not considered and improved. Therefore, new clinical models and organizational approaches are necessary together with a deep technological change, otherwise, theoretical benefits given by telemedicine services, which often employ advanced Information and Communication Technology (ICT) systems and devices, may not be translated into effective enhancements. They are obtained not only through the implementation of single telemedicine services, but integrating them in a wider digital ecosystem, where clinicians are supported in different clinical steps they have to perform.

The present work defines a novel methodological framework based on organizational, clinical and technological innovation, in order to redesign the territorial care for people with chronic diseases. This innovative ecosystem applied in the Italian research project TALIsMAn is based on the concept of a continuum of care and digitalization of CPs supported by Business Process Management System and telemedicine services. The main goal is to organize the different socio-medical activities in a unique and integrated IT system that should be sustainable, scalable and replicable.

This paper aims to explore the lived experience of people with a chronic non-healing wound and to explore what it means to live with a chronic wound.

A descriptive phenomenological study design was adopted to explore the living experience of person with chronic wound. A sample of 15 individuals of both genders was selected using a purposive sampling technique. To collect data, in-depth interviews were conducted, and all the interviews were audio-taped and transcribed verbatim. Data were analysed using the seven-step process described by Colaizzi (1978).

The findings were organized into 6 themes clusters and 12 themes. The six themes clusters were limiting mobility; receiving care; explaining causes of wounds; contending with chronic illnesses; adapting and mal-adapting; and economic burden of the wound.

Chronic wound had a profound impact on participants’ lives by affecting their activities of daily living, their mobility, their income and their personal relationships.

Understanding the lived experiences of people with chronic wounds is crucial for health-care providers, including nurses. Investigating the chronic wound experience has become even more pressing given the projected increase in the number of elderly individuals and those with chronic illnesses such as diabetes mellitus. In Jordan, for example, the prevalence of diabetes mellitus is 17.1%, and it is projected to increase by 2050.

The purpose of this paper is to examine the linkages of employment, chronic disease prevalence and medical care of the older population in India.

This study used the India Human Development Survey data for the analysis. Bivariate, multinomial logit regression and multiple classification analysis are used as methods for the study.

The findings suggest a bi-directional relationship between employment and chronic diseases: the older population who are engaged in regular paid work has lower likelihood to the risk of chronic diseases compared to those who are not working. Conversely, the older population with chronic diseases may be unable to work in regular paid jobs. The greater proportions of not-working older population with savings and retirement pensions are more likely to seek modern treatment for the chronic diseases. Overall, the results foster that employment determines and is determined by chronic disease prevalence among the older population in India.

This paper for the first time presents evidence on the linkages of employment, chronic disease prevalence and medical care of the older population in India by using a unique and comprehensive data source.

Chronic diseases are considered as one of the serious concerns and threats to public health across the globe. Diseases such as chronic diabetes mellitus (CDM), cardio vasculardisease (CVD) and chronic kidney disease (CKD) are major chronic diseases responsible for millions of death. Each of these diseases is considered as a risk factor for the other two diseases. Therefore, noteworthy attention is being paid to reduce the risk of these diseases. A gigantic amount of medical data is generated in digital form from smart healthcare appliances in the current era. Although numerous machine learning (ML) algorithms are proposed for the early prediction of chronic diseases, these algorithmic models are neither generalized nor adaptive when the model is imposed on new disease datasets. Hence, these algorithms have to process a huge amount of disease data iteratively until the model converges. This limitation may make it difficult for ML models to fit and produce imprecise results. A single algorithm may not yield accurate results. Nonetheless, an ensemble of classifiers built from multiple models, that works based on a voting principle has been successfully applied to solve many classification tasks. The purpose of this paper is to make early prediction of chronic diseases using hybrid generative regression based deep intelligence network (HGRDIN) model.

In the proposed paper generative regression (GR) model is used in combination with deep neural network (DNN) for the early prediction of chronic disease. The GR model will obtain prior knowledge about the labelled data by analyzing the correlation between features and class labels. Hence, the weight assignment process of DNN is influenced by the relationship between attributes rather than random assignment. The knowledge obtained through these processes is passed as input to the DNN network for further prediction. Since the inference about the input data instances is drawn at the DNN through the GR model, the model is named as hybrid generative regression-based deep intelligence network (HGRDIN).

The credibility of the implemented approach is rigorously validated using various parameters such as accuracy, precision, recall, F score and area under the curve (AUC) score. During the training phase, the proposed algorithm is constantly regularized using the elastic net regularization technique and also hyper-tuned using the various parameters such as momentum and learning rate to minimize the misprediction rate. The experimental results illustrate that the proposed approach predicted the chronic disease with a minimal error by avoiding the possible overfitting and local minima problems. The result obtained with the proposed approach is also compared with the various traditional approaches.

Usually, the diagnostic data are multi-dimension in nature where the performance of the ML algorithm will degrade due to the data overfitting, curse of dimensionality issues. The result obtained through the experiment has achieved an average accuracy of 95%. Hence, analysis can be made further to improve predictive accuracy by overcoming the curse of dimensionality issues.

The proposed ML model can mimic the behavior of the doctor's brain. These algorithms have the capability to replace clinical tasks. The accurate result obtained through the innovative algorithms can free the physician from the mundane care and practices so that the physician can focus more on the complex issues.

Utilizing the proposed predictive model at the decision-making level for the early prediction of the disease is considered as a promising change towards the healthcare sector. The global burden of chronic disease can be reduced at an exceptional level through these approaches.

In the proposed HGRDIN model, the concept of transfer learning approach is used where the knowledge acquired through the GR process is applied on DNN that identified the possible relationship between the dependent and independent feature variables by mapping the chronic data instances to its corresponding target class before it is being passed as input to the DNN network. Hence, the result of the experiments illustrated that the proposed approach obtained superior performance in terms of various validation parameters than the existing conventional techniques.

Objective. To evaluate a health and fitness programme conducted within a New South Wales, Australia correctional facility for male inmates with a chronic illness. Design. A randomised control trial. Sample. Twenty male inmate participants with a chronic illness, two risk factors for developing a chronic illness or who were over the age of 40 years. Measurements. Pre and post programme health assessments that included resting blood pressure and heart rate, weight, body mass index, waist girth, peak flow measures, peripheral saturation of oxygen, blood glucose levels and 6 minute walk test. Intervention. A 12‐week structured exercise programme focusing on cardio respiratory endurance, strength and flexibility training. Results. Statistically significant improvements in resting heart rate and endurance were found. Conclusions. The health and fitness programme positively impacts on the health of inmates with a chronic illness. A further study with a larger sample size would be productive.

The biopsychosocial model (BPSM) on chronic pain is an interactive psychophysiological behavior pattern that cannot be separated into different independent components. However, the epistemological analysis of the classic BPSM, based on “biopsychosocial factors,” can be reduced to a list of biological, psychological and social factors, which can be addressed simultaneously, but independently, where simultaneity is seen as relationality. The purpose of this paper is to achieve a systemic and transdisciplinary vision of the idea of simultaneity and multidisciplinarity of the BPSM and propose a new model for the diagnosis and treatment of chronic pain.

Based on the following conceptual triad, co-autonomy, centralization and non-requisite variety, to constitute systemic indicators, the authors design a new conceptual model of cohesion, communication, conduction and coordination (CO4) model to deal with the relational system of chronic pain patients.

The indicators of the CO4 system as transdisciplinary structure create and focus a completely new relationship regarding the relational system of the chronic pain patients. This new conceptual framework transcends the objects and frameworks of each discipline separately, going beyond the multidisciplinary model.

The CO4 model allows a diagnostic and therapeutic standardization as a new model on chronic pain, improving therapeutic efficiency, resource use and laying the foundation for a common language in future chronic pain research.

The purpose of this paper is to consider mental health issues in children and adolescents with chronic illness or health conditions, including their treatment, and issues related to delivery of services.

A selective review of the literature was conducted to highlight significant mental health issues and their treatment in youth with various types of chronic illness.

A significant portion of youth experience mental health problems related to their chronic health conditions. While evidence-based treatments are available to address these problems, significant barriers exist that impede the delivery of psychological and behavioral interventions for many youth.

More controlled studies are needed to demonstrate the effectiveness and cost offset of delivering psychological and behavioral interventions for the population of youth with various types of chronic health conditions, particularly in clinical and community settings.

Policy reform can ensure that mental health issues are effectively addressed for children with chronic illness. Policy is needed that promotes integrated health care, whereby psychological and behavioral interventions are delivered in health care settings along with medical interventions to reduce barriers to care.

Significant numbers of children and adolescents have chronic health conditions and many experience mental health problems related to their conditions. While evidence-based treatments are available to address these problems, significant barriers impede the delivery of psychological and behavioral interventions for many youth. Health care policy promoting integrated health care to deliver psychological and behavioral interventions in health care settings along with medical interventions should reduce barriers to care and improve both physical and mental health outcomes for youth.

The viewpoint essay focusses on the significance of integrated care (IC) for chronic pain in India, in an attempt to reflect on how pain management and care can be made more accessible and available to patients.

This reflective essay invites looking at chronic pain beyond biomedical perspectives. Insights from the medical humanities and the social sciences are used to emphasise chronic pain as a psychosocial and socio-political phenomenon and not just a biomedical category.

The essay argues that there are several challenges and barriers to the recognition and validation of chronic pain as a speciality.

IC has not received sufficient attention in the Indian context, where medical curricula and training do not sufficiently include an understanding of the multi-faceted aspects surrounding chronic pain. By highlighting the role of humanistic approaches to effectively bridge the gap, this viewpoint essay illustrates the significance of drawing on an integrated or holistic healthcare framework.

Contrary to want-based services, customer participation has got lesser attention in high-credence services like health care. Customer participation for patients with chronic illnesses could be life-threatening and goes beyond the service organization’s physical environment. Realizing the importance of transformative service research in health-care services, this study aims to propose and validate the conceptualization of customer participation for patients with chronic illnesses.

The study uses sequential exploratory research design with mixed method research. The first phase is a qualitative exploration of the nature and meaning of customer participation by synthesizing theory and insights from semi-structured interviews (N = 75) with doctors, patients and paramedical staff. Next, survey data (N = 690) of patients with chronic illnesses is used to validate the proposed conceptualization. Finally, nomological validity was also tested on an additional survey data set (N = 362) using SEM and FsQCA.

The findings reveal that health-care customer participation is a three-dimensional behavioral construct in which a customer can participate by sharing information, involving in decision-making and ensuring compliance. The study also demonstrates that customer participation is a critical driver of satisfaction with life and perceived control on illness.

The research provides policy guidelines for owners and operators of health-care organizations in developing frameworks for collecting participation data, which can be used in strategies for seeking customer participation.

The research conceptualizes and validates “customer participation” as a multidimensional higher-order construct for patients with chronic illnesses, rarely focused in services marketing and management research on health care.

This study aims to synthesize the existing serious games designed to promote mental health in adolescents with chronic illnesses.

This study conducted a review following the guidelines of Joanna Briggs Institute and Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews. Searches were conducted in databases PubMed, Scopus, Web of Science, Cochrane Library, cumulative index to nursing and allied health literature, PsycINFO, China national knowledge infrastructure Wanfang, VIP Database for Chinese Technical Periodicals and SinoMed from inception to February 12, 2023.

A total of 14 studies (describing 14 serious games) for improving the mental health of adolescents with chronic diseases were included. Of all the included games, 12 were not described as adopting any theoretical framework or model. The main diseases applicable to serious games are cancer, type 1 diabetes and autism spectrum disorder. For interventional studies, more than half of the study types were feasibility or pilot trials. Furthermore, the dosage of serious games also differs in each experiment. For the game elements, most game elements were in the category “reward and punishment features” (n = 50) and last was “social features” (n = 4).

Adolescence is a critical period in a person’s physical and mental development throughout life. Diagnosed with chronic diseases during this period will cause great trauma to the adolescents and their families. Serious game interventions have been developed and applied to promote the psychological health field of healthy adolescents. To the best of the authors’ knowledge, this study is the first to scope review the serious game of promoting mental health in the population of adolescents with chronically ill. At the same time, the current study also extracted and qualitatively analyzed the elements of the serious game.