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The prison population is seldom studied and often overlooked in many countries despite their vulnerability to long-term illness. This study aims to explore the factors associated with the non-treatment for long-term illnesses among incarcerated individuals.

This study is a cross-sectional analysis. The authors conducted a secondary data analysis using information collected in the Peruvian census of incarcerated individuals. The study population consisted of incarcerated individuals diagnosed with a long-term illness. To evaluate the factors associated with non-treatment, the authors used a Poisson regression model.

The authors included 12,512 incarcerated individuals (age: 40.9 ± 13.1 years), and 39% of them did not receive treatment for their long-term illness. The authors observed that non-treatment was statistically associated with gender, age, having children, use of the Spanish language, sexual identity, judicial situation, penitentiary location, discrimination inside the penitentiary and health insurance before incarceration. However, only having children (prevalence ratio [PR]: 1.11, confidence interval [CI]95% 1.03–1.19), using the Spanish language (PR: 1.15, CI95%: 1.01–1.31), being in a penitentiary not in Lima (PR: 1.11, CI95%: 1.06–1.17) and perceiving discrimination inside the penitentiary (PR: 1.12, CI95% 1.06–1.18) increased the prevalence of non-treatment.

Identifying the factors associated with non-treatment will allow us to implement measures for prioritizing groups and developing strategies for the evaluation, close follow-up of their health and management of comorbidities.

Diabetes is one of the life-threatening chronic diseases, which is already affecting 422m people globally based on (World Health Organization) WHO report as at 2018. This costs individuals, government and groups a whole lot; right from its diagnosis stage to the treatment stage. The reason for this cost, among others, is that it is a long-term treatment disease. This disease is likely to continue to affect more people because of its long asymptotic phase, which makes its early detection not feasible.

In this study, the authors have presented machine learning models with feature selection, which can detect diabetes disease at its early stage. Also, the models presented are not costly and available to everyone, including those in the remote areas.

The study result shows that feature selection helps in getting better model, as it prevents overfitting and removes redundant data. Hence, the study result when compared with previous research shows the better result has been achieved, after it was evaluated based on metrics such as F-measure, Precision-Recall curve and Receiver Operating Characteristic Area Under Curve. This discovery has the potential to impact on clinical practice, when health workers aim at diagnosing diabetes disease at its early stage.

This study has not been published anywhere else.

The primary objective of this study is to investigate the cognitive aspects of spatial experiences of paediatric inpatients who receive long-term treatment in a healthcare setting in relation to the syntactic parameters of healthcare environment. It is aimed to investigate how the change in the child’s cognition caused by the environmental stress experienced by the child during his/her stay in the hospital is related to the physical parameters of the treatment space.

The methodology of the study is based on a correlational analysis to identify the cognitive and syntactic factors of the healthcare environment that contribute to changes in the perceptual processes of a sample group of thirty children. The study examined the relationships between the graph and isovist variables, and the cognitive parameters of paediatric inpatients. The two datasets were subjected to regression analyses in order to identify any significant findings, which allowed for a discussion of how the patients’ changing perceptual processes are influenced by the syntactic measures of the healthcare setting.

The study showed that a syntactically intelligible floor plan contributes significantly to reducing environmental stress among paediatric inpatients. The presence of shared spaces within the healthcare environment, where social interaction with peers is possible, emerges as a crucial factor influencing children’s spatial perception. Additionally, the visibility characteristics of shared spaces may also play a key role in enhancing children’s perceptions of safety.

The limitations of the study include the fact that the study was conducted in an oncology and haematology inpatient unit with challenging conditions in terms of the mobility potentials of the children, which might have affected their perceptual processes. A further limitation is that the sample size comprised only 30 children, and the spatial configuration of the healthcare environment was linear and not particularly complex.

By identifying the impact of spatial design on children’s well-being, the study informs the creation and improvement of healthcare environments. Enhanced understanding of factors like intelligible floor plans, shared spaces and isovist values can lead to more child-friendly facilities, potentially alleviating stress for young patients. Consequently, this research may contribute to improved healthcare outcomes, increased comfort for paediatric inpatients, and a more supportive environment for their families, fostering a holistic approach to paediatric care and positively influencing the overall quality of life for children undergoing long-term treatment.

This study contributes to the theoretical discourse on how the constrained physical conditions of a paediatric healthcare environment may influence the perceptual processes of paediatric inpatients. The results of this evidence-based study have the potential to inform the evaluation of design guidelines for healthcare settings, with the ultimate aim of enhancing therapeutic environments.

The case is designed to be used with the digital business model framework developed by Peter Weill and Stephanie Woerner of Massachusetts Institute of Technology (MIT) (Weill and Woerner, 2015) and is referred to as the W & W framework. This approach provides a useful structure for thinking through the strategic options facing environments ripe for digital transformation.

Research for this case was conducted through face-to-face interviews with the protagonist, as well as through a review of their business planning documents and other data and documentation provided by the founder. Some of the market and industry data were obtained using secondary research and industry reports. Interviews were digitally recorded and transcribed to ensure accuracy.

The case follows the story of Kurt Waltenbaugh, a Minnesota entrepreneur who shared the dream of using data analytics to reduce costs within the US health-care system. In early 2014, Waltenbaugh and a physician colleague founded Carrot Health to bring together their personal experience and expertise in both consumer data analytics and health care. From the beginning, they focused on how to use data analytics to help identify high-risk/high-cost patients who had not yet sought medical treatment. They believed that they could use these insights to encourage early medical interventions and, as a result, lower the long-term cost of care.

Carrot’s initial success found them in a consultative role, working on behalf of insurance companies. Through this work, they honed their capabilities by helping their clients combine existing claims data with external consumer behavioral data to identify new potential customers. These initial consulting contracts gave Carrot the opportunity to develop its analytic tools, business model and, importantly, to earn some much-needed cash flow during the start-up phase. However, they also learned that, while insurance companies were willing to purchase data insights for one-off market expansion projects, it was much more difficult to motivate them to use data proactively to eliminate costs on an ongoing basis. Waltenbaugh believed that Carrot’s greatest potential lay in their ability to develop predictive models of health outcomes, and this case explores Carrot’s journey through strategic decisions and company transformation.

This case is intended for either an undergraduate or graduate course on entrepreneurial strategy. It provides an effective introduction to the unique structure and constraints which apply to an innovative start-up within the health-care industry. The case also serves as a platform to explore the critical criteria to be considered when developing a digital transformation strategy and exposing students to the digital business model developed by Weill and Woerner (2015) at MIT (referred to in this instructor’s manual as the W&W framework). The case was written to be used in an advanced strategy Master of Business Administration (MBA) class, an undergraduate specialty health-care course or as part of a health-care concentration in a regular MBA, Master of Health Care Administration (MHA) or Master of Public Health (MPH). It may be taught toward the end of a course on business strategy when students are building on generic strategy frameworks and adapting their strategic thinking to the characteristics of specific industries or sectors. However, the case can also be taught as part of a course on health-care innovation in which case it also serves well as an introduction to the health-care payments and insurance system in the USA. Finally, the case can be used in a specialized course on digital transformation strategy in which case it serves as an introduction to the MIT W&W framework.

The case is particularly well-suited to students who are familiar with traditional frameworks for business strategy and business models. The analysis builds on this knowledge and introduces students interested in learning about the opportunities and challenges of digital strategy. Equally, the case works well for students with clinical backgrounds, who are interested in how business strategy can influence changes within the health-care sphere. Finally, an important aspect of the case design was to develop students’ analytical confidence by encouraging them to “get their hands dirty” and to carry out some basic exploratory data analytics themselves. As such, the case requires students to combine and correlate data and to experience the potentially powerful combination of clinical and consumer data. Instructors should find that the insights from these activities give students unique insights into the potential for of data analytics to move health care from a reactive/treatment ethos to a proactive/intervention ethos. This experience can be particularly revealing for students with clinical backgrounds who may initially be resistant to the use of clinical data by commercial organizations.

Mentalization-based treatment (MBT) is a psychotherapeutic approach that aims to increase mentalizing capacity. The purpose of this meta-ethnography was to synthesize the available qualitative literature on MBT to allow for a more thorough understanding of the lived experience of those who have undergone this therapy.

A systematic search of seven databases was carried out. The Critical Appraisal Skills Programme was used to appraise the papers suitable for inclusion. The data were synthesized using a meta-ethnographic approach in which the second-order constructs from each paper were translated and reinterpreted creating a line of argument synthesis.

A total of 11 studies were included in the meta-ethnography. Three overarching themes were identified within the included papers which outlined that participant experience of MBT consisted of three different developmental stages. Navigating the therapeutic process describes the participant’s experience of the therapeutic process of MBT. The processes of change in MBT outlined participant reports of mechanisms of change experienced in MBT. Mentalizing self and others described the experience of generalizing new knowledge and skills to the world outside of therapy and unveiled the impact that engaging in MBT had on participants.

This meta-ethnography offers new insights into how clients experience MBT as a therapeutic process and offers suggestions for implementation in clinical practice as well as areas of focus for research of this therapeutic approach.

Customer lifetime value (CLV) is one of the key indicators to measure the success or health of an organization. How can an organization assess the organization's customers' lifetime value (LTV) and offer relevant strategies to retain prospective and profitable customers? This study offers an integrated view of different methods for calculating CLVs for both loyalty members and non-membership customers.

This study outlines eleven methods for calculating CLV considering (1) the deterministic aspect of NPV (Net present value) models in both finite and infinite timespans, (2) the geometric pattern and (3) the probabilistic aspect of parameter estimates through simulation modeling along with (4) the migration models for including “the probability that customers will return in the future” as a key input for CLV calculation.

The CLV models are validated in the context of complementary and alternative medicine (CAM)in the healthcare industry. The results show that understanding CLV can help the organization develop strategies to retain valuable customers while maintaining profit margins.

The integrated CLV models provide an overview of the mathematical estimation of LTVs depending on the nature of the customers and the business circumstances and can be applied to other business settings.

This study is a radical interactionist analysis of family conflict. Drawing on both a negotiated order perspective and Athen's theory of complex dominative encounters, this study analyzes the role that domination plays in conflicts among intimates. As the family engages in repeated conflicts over roles, the family also engages in negotiations over the family order, what role each party should play, interpretations of past events, and plans for the future. These conflicts take place against a backdrop of patriarchy that asymmetrically distributes power in the family to determine the family order. The data from this study come from a content analysis of mothers with substance use problems as depicted in the reality television show Intervention. The conflicts in these families reveal that these families develop a grinding family order in which families engaged in repeated conflict but also continued to operate as and identify as a family. These conflicts are shaped by and reinforce patriarchal expectations that mothers are central to family operation. The intervention at the end of each episode offered an opportunity for the family to engage in a concerted campaign to try to force the mother into treatment and reestablish the family order.

The purpose of this paper is to investigate the effect of plasma electrolytic oxidation (PEO) coatings and sealed PEO coatings on the corrosion resistance and cytocompatibility of a novel Mg-1Zn-0.45Ca alloy in simulated body fluid (SBF).

The microstructure, corrosion resistance and cytocompatibility of PEO coatings and phosphate conversion-treated PEO coatings were investigated and was compared with the bare Mg alloy.

The hot-extruded Mg-Zn-Ca alloy exhibit inhomogeneous microstructure and suffered from localized corrosion in the SBF. The PEO coating after phosphate conversion treatment offers enhanced protectiveness to the Mg alloy within an immersion period of up to 60 days, which is significantly improved compared with the performance of the PEO-coated Mg alloy, but the cytocompatibility was slightly decreased.

This work offers new perspective in balancing the protectiveness and cytocompatibility of bio-materials.

This paper aims to report on the results of a global search to identify the characteristics of successful sexual offender treatment programs, with a view to providing guidance for program development.

A keyword search was conducted of criminology and social science databases. Successful programs were selected on evaluations that used standard scientific designs.

This study identified 18 evaluations of 16 programs showing significant reductions in reconvictions. Most programs used cognitive behavioural therapy (CBT), with both group and individual sessions; and many evidenced multisystemic therapy (MST) approaches involving families and/or local communities. CBT-based approaches were also common in the 20 unsuccessful programs identified in the study, although fewer MST-oriented features were in evidence. Noncustodial settings, and combined custodial-noncustodial settings, were also more prominent in the successful programs.

There is a shortage of studies focused on the specific components of successful treatment programs for sexual offenders, including for subsets of offenders, such as ethnic minority groups and women.

The findings demonstrate the need for more investment in treatment programs with strict evaluation processes. New and modified programs are likely to benefit from the application of CBT, MST and a community-based reintegration component. More research is needed on effective elements of sexual offender treatment programs.

To the best of the authors’ knowledge, this appears to be the first study that examines features of successful sexual offender treatment programs, compared to unsuccessful programs, using a case-study approach. The findings reinforce the known value of CBT and systemic approaches as core features of programs but raise important questions about what other components are key to activating success.