Management Of Chronic Conditions Research Articles

A novel CNN-based image segmentation pipeline for individualized feline spinal cord stimulation modeling.

Spinal cord stimulation (SCS) is a well-established treatment for the management of certain chronic pain conditions. More recently, it has also garnered attention as a means of modulating neural activity with the goal of restoring lost autonomic or sensory-motor function. Personalized modeling and treatment planning are critical aspects of safe and effective SCS [46, 60]. However, the generation of spine models at the required level of detail and accuracy requires time and labor intensive manual image segmentation by human experts. Hence, there is a need for maximally automated segmentation routines capable of producing high-quality anatomical models that can be used even in cases where available data is limited. To this end, we developed an automated image segmentation and model generation pipeline based on a novel Convolutional Neural Network (CNN) architecture trained on feline spinal cord magnetic resonance imaging (MRI) data. The pipeline includes steps for image preprocessing, data augmentation, transfer learning and cleanup. To assess the relative importance of each step in the pipeline and of our choice of CNN architecture, we systematically dropped steps or substituted architectures, quantifying the downstream effects in terms of tissue segmentation quality (Jaccard index and Hausdorff distance) and predicted nerve recruitment (estimated axonal depolarization). This leaveone-out analysis demonstrated that each pipeline step contributed a small but measurable increment to mean segmentation quality. Surprisingly, minor differences in segmentation accuracy translated to significant deviations (ranging between 4% and 13% for each pipeline step) in predicted nerve recruitment, highlighting the importance of careful workflow design. To our knowledge, this is the first analysis to also assess the downstream impact of segmentation quality differences on neurostimulation predictions. Furthermore, transfer learning techniques enhanced segmentation metric consistency and allowed generalization to a completely different spine region with minimal additional training data. This work helps pave the way towards fully automated, personalized SCS treatment planning in clinical settings.

MigraineTracker: Examining Patient Experiences with Goal-Directed Self-Tracking for a Chronic Health Condition.

Self-tracking and personal informatics offer important potential in chronic condition management, but such potential is often undermined by difficulty in aligning self-tracking tools to an individual's goals. Informed by prior proposals of goal-directed tracking, we designed and developed MigraineTracker, a prototype app that emphasizes explicit expression of goals for migraine-related self-tracking. We then examined migraine patient experiences in a deployment study for an average of 12+ months, including a total of 50 interview sessions with 10 patients working with 3 different clinicians. Patients were able to express multiple types of goals, evolve their goals over time, align tracking to their goals, personalize their tracking, reflect in the context of their goals, and gain insights that enabled understanding, communication, and action. We discuss how these results highlight the importance of accounting for distinct and concurrent goals in personal informatics together with implications for the design of future goal-directed personal informatics tools.

The Development and Implementation of a Competency-Focused Curriculum in Health and Exercise Sciences

Historically, undergraduate programs in Health and Exercise Sciences (i.e. Kinesiology) are rooted in common areas such as physiology, anatomy, biomechanics, motor control, psychology, nutrition, and rehabilitation. A typical four-year program offers a general education across these areas often delivering a breadth of knowledge in many areas, albeit often lacking in transferable technical skill that relates to industry. With many graduates now pursuing advanced training in professional programs there is a need to develop more competency-focused curricula to better prepare students for entry into professional fields. Further, overburdened healthcare systems worldwide combined with an ageing population find themselves with a gap in service delivery, given the growing body of evidence supporting the benefits of high-quality exercise training in the prevention, treatment and management of chronic conditions. In 2018, following feedback from provincial ministries, the University Senate, faculty, students, and community partners, the School of Health and Exercise Sciences at the University of British Columbia Okanagan underwent a strategic review. This review led to the development of a professionally focused, competency-based program, now known as the Bachelor of Health and Exercise Sciences. Within this program are three concentrations geared towards developing knowledge and skills in differing areas dependent on student interest and desired career path: Kinesiology and Allied Health, Health Behaviour Change, and Clinical Exercise Physiology. The development of the revised curriculum involved crucial components such as defining new program and concentration level learning outcomes, competency profiles, definitions, progressions, and practical assessment strategies. Additionally, each concentration integrates a community practicum designed to enhance mastery of competencies within a professional setting. Establishing these practicums necessitates ongoing collaborative efforts with both existing and new community partners, the formulation of standards, and the implementation of a process to ensure students possess a baseline skill level before engaging with the community. A substantial challenge in the revised curriculum is the instruction of technical skills in a lab environment, as well as effective practical skill assessment that meets industry standards, for upwards of 200 students. To this end a great deal of planning was required from a resources standpoint, onboarding of new faculty with industry experience, as well as alignment with pre-existing certifying bodies including the American College of Sports Medicine, Exercise & Sport Science Australia, and the Canadian Society for Exercise Physiology. Looking to the future we anticipate both challenges and opportunities as we continue to redefine professional competencies and remap them throughout the curriculum to enhance skill progression and ensure our graduates are fit for purpose. Further, we are excited to continue to work alongside provincial entities and existing certifying bodies as we look toward the professionalization of the field. Lastly, but up utmost importance, is the dissemination of our process to other organizations and institutions in hopes to build momentum in the quickly evolving academic and professional landscape of Health and Exercise Sciences. None. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Undiagnosed HIV in Patients on Immunosuppressive Medications Presenting with HIV-Associated Kidney Disease.

Approximately 158,500 adults and adolescents in the United States live with undiagnosed human immunodeficiency virus (HIV). Missed or delayed diagnoses adversely affect disease management and outcomes. This is particularly salient for patients receiving immunosuppressive and immunomodulatory therapy for the management of chronic inflammatory conditions, in which additional immunosuppression may increase the risk and severity of opportunistic infections. Despite this risk, comprehensive HIV testing before the initiation of immunosuppressive therapy is not yet the norm. We describe a case series containing the narratives of three patients recently treated with immunosuppressive agents, who presented with signs concerning for HIV-associated kidney diseases and who were found to have undiagnosed HIV later in the treatment course, which, unfortunately, resulted in poor outcomes. Screening for HIV or related illnesses, such as viral hepatitis or mycobacterial co-infections including tuberculosis, is essential before initiating biologic immunosuppression.

Integrating a Community-Based Health Information System with a Patient-Centered Medical Home to improve care of patients with hypertension: a longitudinal observational study protocol

BackgroundThe primary healthcare system in Pakistan focuses on providing episodic, disease-based care. Health care for low-middle income communities is largely through a fee-for-service model that ignores preventive and health-promotive services. The growing burden of cardiovascular illnesses requires restructuring of the primary health care system allowing a community-to-clinic model of care to improve patient- and community-level health indicators.MethodsWe propose a model that integrates a Patient-Centered Medical Home (PCMH) with a Community-Based Health Information System (CBHIS) using hypertension (HTN) as an example. This protocol describes the integration and evaluation of the PCMH-CBHIS infrastructure through a population-based, observational, longitudinal study in a low-middle income, urban community in Pakistan. Participants are being enrolled in CBHIS and will be followed longitudinally over two years for HTN outcomes. A mixed-methods approach is adopted to evaluate the process of integrating PCMH with CBHIS. This involves building partnerships with the community through formal and informal meetings, focus group discussions, and a household health assessment survey (HAS). Community members identified with HTN are linked to PCMH for disease management. A customized electronic medical record system links community-level data with patient-level data to track changes in disease burden. The RE-AIM evaluation framework will be used to monitor community and individual-level metrics to guide implementation assessment, the potential for generalization, and the effectiveness of the PCMH in improving HTN-related health outcomes. Ethical clearance has been obtained from the Ethics Review Committee at Aga Khan University (2022-6723-20985).DiscussionThis study will evaluate the value of restructuring the primary care health system by ensuring systematic community engagement and measurement of health indicators at the patient- and community-level. While HTN is being used as a prototype to generate evidence for the effectiveness of this model, findings from this initiative will be leveraged towards strengthening the management of other acute and chronic conditions in primary care settings. If effective, the model can be used in Pakistan and other LMICs and resource-limited settings.

Telehealth Utilization and Associations in the United States During the Third Year of the COVID-19 Pandemic: Population-Based Survey Study in 2022.

The COVID-19 pandemic rapidly changed the landscape of clinical practice in the United States; telehealth became an essential mode of health care delivery, yet many components of telehealth use remain unknown years after the disease's emergence. We aim to comprehensively assess telehealth use and its associated factors in the United States. This cross-sectional study used a nationally representative survey (Health Information National Trends Survey) administered to US adults (≥18 years) from March 2022 through November 2022. To assess telehealth adoption, perceptions of telehealth, satisfaction with telehealth, and the telehealth care purpose, we conducted weighted descriptive analyses. To identify the subpopulations with low adoption of telehealth, we developed a weighted multivariable logistic regression model. Among a total of 6252 survey participants, 39.3% (2517/6252) reported telehealth use in the past 12 months (video: 1110/6252, 17.8%; audio: 876/6252, 11.6%). The most prominent reason for not using telehealth was due to telehealth providers failing to offer this option (2200/3529, 63%). The most common reason for respondents not using offered telehealth services was a preference for in-person care (527/578, 84.4%). Primary motivations to use telehealth were providers' recommendations (1716/2517, 72.7%) and convenience (1516/2517, 65.6%), mainly for acute minor illness (600/2397, 29.7%) and chronic condition management (583/2397, 21.4%), yet care purposes differed by age, race/ethnicity, and income. The satisfaction rate was predominately high, with no technical problems (1829/2517, 80.5%), comparable care quality to that of in-person care (1779/2517, 75%), and no privacy concerns (1958/2517, 83.7%). Younger individuals (odd ratios [ORs] 1.48-2.23; 18-64 years vs ≥75 years), women (OR 1.33, 95% CI 1.09-1.61), Hispanic individuals (OR 1.37, 95% CI 1.05-1.80; vs non-Hispanic White), those with more education (OR 1.72, 95% CI 1.03-2.87; at least a college graduate vs less than high school), unemployed individuals (OR 1.25, 95% CI 1.02-1.54), insured individuals (OR 1.83, 95% CI 1.25-2.69), or those with poor general health status (OR 1.66, 95% CI 1.30-2.13) had higher odds of using telehealth. To our best knowledge, this is among the first studies to examine patient factors around telehealth use, including motivations to use, perceptions of, satisfaction with, and care purpose of telehealth, as well as sociodemographic factors associated with telehealth adoption using a nationally representative survey. The wide array of descriptive findings and identified associations will help providers and health systems understand the factors that drive patients toward or away from telehealth visits as the technology becomes more routinely available across the United States, providing future directions for telehealth use and telehealth research.

Whole-cycle management of women with epilepsy of child-bearing age: ontology construction and application.

The effective management of epilepsy in women of child-bearing age necessitates a concerted effort from multidisciplinary teams. Nevertheless, there exists an inadequacy in the seamless exchange of knowledge among healthcare providers within this context. Consequently, it is imperative to enhance the availability of informatics resources and the development of decision support tools to address this issue comprehensively. The development of the Women with Epilepsy of Child-Bearing Age Ontology (WWECA) adhered to established ontology construction principles. The ontology's scope and universal terminology were initially established by the development team and subsequently subjected to external evaluation through a rapid Delphi consensus exercise involving domain experts. Additional entities and attribute annotation data were sourced from authoritative guideline documents and specialized terminology databases within the respective field. Furthermore, the ontology has played a pivotal role in steering the creation of an online question-and-answer system, which is actively employed and assessed by a diverse group of multidisciplinary healthcare providers. WWECA successfully integrated a total of 609 entities encompassing various facets related to the diagnosis and medication for women of child-bearing age afflicted with epilepsy. The ontology exhibited a maximum depth of 8 within its hierarchical structure. Each of these entities featured three fundamental attributes, namely Chinese labels, definitions, and synonyms. The evaluation of WWECA involved 35 experts from 10 different hospitals across China, resulting in a favorable consensus among the experts. Furthermore, the ontology-driven online question and answer system underwent evaluation by a panel of 10 experts, including neurologists, obstetricians, and gynecologists. This evaluation yielded an average rating of 4.2, signifying a positive reception and endorsement of the system's utility and effectiveness. Our ontology and the associated online question and answer system hold the potential to serve as a scalable assistant for healthcare providers engaged in the management of women with epilepsy (WWE). In the future, this developmental framework has the potential for broader application in the context of long-term management of more intricate chronic health conditions.

Understanding the implementation and sustainability needs of evidence-based programs for racial and ethnic minoritized older adults in under-resourced communities with limited aging services

BackgroundEvidence-based programs (EBPs) for older adults effectively improve health outcomes. However, there is a limited understanding of the unique needs of service providers as they consider adopting, implementing, and maintaining programs for older minority adults in low-income communities with limited aging services.MethodsWe conducted semi-structured interviews with key informants of community-based organizations (CBOs) to understand implementation and sustainability needs of CBOs within four racial and ethnically diverse Los Angeles County geographic areas. We performed thematic analysis of interview transcripts.ResultsInterviews were conducted with representatives from 25 senior-serving agencies providing aging-related EBPs. CBO representatives reported implementing EBPs in 8 domains: Falls Prevention (68%), Mental Health (64%), Caregiver Health (48%), Chronic Disease Management (48%), Diabetes Management (36%), Arthritis Management (28%), Physical Activity (24%), and Multiple Conditions Management (8%). Themes are presented using the six domains of the Bass and Judge framework for factors impacting successful and sustained EBP implementation. CBOs in low-income and diverse communities described unique challenges with tailoring interventions based on local community context (literacy, language), cultural context, and locally available resources (technology, safe community spaces, transportation) and faced resource-intensive administrative burdens through staff turnover, data collection, sustainable funding, and networking.ConclusionsServing racial and ethnic communities has unique challenges that require tailored approaches and additional resources to ensure equitable access to EBPs for all communities. We describe suggestions for enhancing the effective adoption of EBPs among service agencies in under-resourced and diverse aging communities serving populations with aging-related health disparities.

Chronic Disease Patterns and Their Relationship With Health-Related Quality of Life in South Korean Older Adults With the 2021 Korean National Health and Nutrition Examination Survey: Latent Class Analysis.

Improved life expectancy has increased the prevalence of older adults living with multimorbidities, which likely deteriorates their health-related quality of life (HRQoL). Understanding which chronic conditions frequently co-occur can facilitate person-centered care tailored to the needs of individuals with specific multimorbidity profiles. The study objectives were to (1) examine the prevalence of multimorbidity among Korean older adults (ie, those aged 65 years and older), (2) investigate chronic disease patterns using latent class analysis, and (3) assess which chronic disease patterns are more strongly associated with HRQoL. A sample of 1806 individuals aged 65 years and older from the 2021 Korean National Health and Nutrition Examination Survey was analyzed. Latent class analysis was conducted to identify the clustering pattern of chronic diseases. HRQoL was assessed by an 8-item health-related quality of life scale (HINT-8). Multiple linear regression was used to analyze the association with the total score of the HINT-8. Logistic regression analysis was performed to evaluate the odds ratio of having problems according to the HINT-8 items. The prevalence of multimorbidity in the sample was 54.8%. Three chronic disease patterns were identified: relatively healthy, cardiometabolic condition, arthritis, allergy, or asthma. The total scores of the HINT-8 were the highest in participants characterized as arthritis, allergy, or asthma group, indicating the lowest quality of life. Current health care models are disease-oriented, meaning that the management of chronic conditions applies to a single condition and may not be relevant to those with multimorbidities. Identifying chronic disease patterns and their impact on overall health and well-being is critical for guiding integrated care.

Redefining Healthcare With Artificial Intelligence (AI): The Contributions of ChatGPT, Gemini, and Co-pilot.

Artificial Intelligence (AI) in healthcare marks a new era of innovation and efficiency, characterized by the emergence of sophisticated language models such as ChatGPT (OpenAI, San Francisco, CA, USA), Gemini Advanced (Google LLC, Mountain View, CA, USA), and Co-pilot (Microsoft Corp, Redmond, WA, USA). This review explores the transformative impact of these AI technologies on various facets of healthcare, from enhancing patient care and treatment protocols to revolutionizing medical research and tackling intricate health science challenges. ChatGPT, with its advanced natural language processing capabilities, leads the way in providing personalized mental health support and improving chronic condition management. Gemini Advanced extends the boundary of AI in healthcare through data analytics, facilitating early disease detection and supporting medical decision-making. Co-pilot, by integrating seamlessly with healthcare systems, optimizes clinical workflows and encourages a culture of innovation among healthcare professionals. Additionally, the review highlights the significant contributions of AI in accelerating medical research, particularly in genomics and drug discovery, thus paving the path for personalized medicine and more effective treatments. The pivotal role of AI in epidemiology, especially in managing infectious diseases such as COVID-19, is also emphasized, demonstrating its value in enhancing public health strategies. However, the integration of AI technologies in healthcare comes with challenges. Concerns about data privacy, security, and the need for comprehensive cybersecurity measures are discussed, along with the importance of regulatory compliance and transparent consent management to uphold ethical standards and patient autonomy. The review points out the necessity for seamless integration, interoperability, and the maintenance of AI systems' reliability and accuracy to fully leverage AI's potential in advancing healthcare.

Common barriers and enablers to the use of non-drug interventions for managing common chronic conditions in primary care: an overview of reviews

BackgroundNon-drug interventions are recommended for chronic condition prevention and management yet are underused in clinical practice. Understanding barriers and enablers to using non-drug interventions may help implement non-drug interventions in primary care. We aimed to conduct an overview of reviews to identify and summarise common barriers and enablers for using non-drug interventions for common chronic conditions in primary care.MethodsWe included qualitative and quantitative reviews that used systematic process or methods to examine barriers and enablers to using non-drug interventions for chronic condition prevention and management in primary care settings. We searched 5 electronic databases (PubMed, Cochrane Database of Systematic Reviews, EMBASE, PsycInfo and CINAHL) from inception to September 2022. Two authors independently screened reviews. One author extracted and deductively coded data to Consolidated Framework of Implementation Research (CFIR) (and where relevant, Theoretical Domains Framework [TDF]). A second author validated 10% of extracted data and coding. Data was synthesised thematically using CFIR and TDF. One author assessed the methodological quality of included reviews using a modified AMSTAR 2 tool, with 10% validated by a second author. We assessed overlap between primary studies in included reviews.ResultsFrom 5324 records, we included 25 reviews, with data predominately from patients. Overall, 130 subthemes (71 barrier and 59 enabler) were identified across 4 CFIR domains (Innovation, Outer Setting, Inner Setting, and Individuals), and all TDF domains. Common barrier and enabler subthemes were identified for CFIR constructs of Innovation Adaptability, Innovation Cost, Innovation Relative Advantage, Local Attitudes, External Pressure, Local Conditions, Relational Connections, Available Resources, and Access to Knowledge and Information. For TDF domains, important barrier and enabler subthemes were identified for Knowledge, Skills, Environmental Context and Resources, Beliefs about Consequences, Reinforcement, and Emotion.ConclusionsWe synthesised reviews to provide new insight into common barriers and enablers for using non-drug interventions to prevent and manage chronic conditions in primary care. The factors identified can inform the development of generalisable implementation interventions to enhance uptake of multiple non-drug interventions simultaneously.Trial RegistrationThis study was registered in PROSPERO (CRD42022357583).

Socio-technical platforms for care transformation: An integrative synthesis and conceptualization

This study is at the intersection of two trends in healthcare, integrated care (IC) and digitalization. These advancements aim to mitigate challenges associated with the management of chronic and multimorbid conditions which form the bulk of healthcare expenditure. Rampant fragmentation in service provisioning and technological innovation result in inefficent and increasingly burdened healthcare systems. Addressing fragmentation, IC models show promise and stand to benefit greatly from emerging digital health platform solutions. However, these interventions are relatively nascent and lack comprehensive analysis. Therefore, this study explores these emerging solutions with an integrative literature review and a qualitative analysis, identifying 26 comprehensive platform solutions that enable coordination in chronic care ecosystems. The findings offer a detailed overview and an integrative synthesis that conceptualizes socio-technical solution architectures, integrating the elements of people, process, and technology within a multi-level IC framework. This sheds light on the complex orchestration needed for managing cross-provider solutions for chronic care, and it helps researchers and decision makers better understand the complexity and challenges of healthcare transformation. Development barriers and gaps for further research are also explored.

Home Medication Management and Practices among Post-stroke Patients: A Cross-sectional Study in a University-based Primary Care Clinic in Malaysia

Effective medication management practice (MMP) improves compliance of chronic conditions management and reduces medication error for better clinical outcomes. This is important for stroke survivors with multiple comorbidities and post-stroke complications. This study aimed to determine appropriateness of home MMP and its associated factors among post stroke patients. This was a cross-sectional, single-centre study involving 120 stroke patients of a primary care medical centre in Kuala Lumpur between January and March 2021. The assessment of MMP appropriateness relied on scores obtained through a set of questions administered via face-to-face, online or telephone interview. The mean age of participants was 65.1 (SD 11.7) years. 55.8% of participants had inappropriate home MMP; where the majority did not update their medication list (86.3%), did not memorise the medication’s name (75%), and did not return the leftover medication to the pharmacy (63.3%). Female gender (AOR: 2.74, 95% CI: 1.18-6.35, p-value: 0.019), household income (> RM4850) (AOR: 2.82, 95% CI: 1.03-7.69, p-value: 0.043), and number of clinic appointments (>2) (AOR: 5.27, 95% CI: 1.44-19.24, p-value: 0.012) were significantly correlated with better home MMP. The MMP among post-stroke patients was poor. Better home MMP were associated with female gender, higher socioeconomic status, and more frequent clinic appointments. Concerted health education should be provided, particularly focusing on medication management to improve home MMP in post-stroke patients and ultimately improving their overall health outcomes.

The Role of Physiotherapy in Managing Chronic Respiratory Conditions: A Comprehensive Review

Chronic respiratory conditions, including Chronic Obstructive Pulmonary Disease (COPD) and interstitial lung disease, present persistent challenges to respiratory function and holistic well-being. This paper acknowledges the complexity of these conditions and underscores the essential role of physiotherapy interventions within multidisciplinary care approaches. To provide a comprehensive understanding of the management of chronic respiratory conditions, this review explores key physiotherapy interventions such as breathing exercises, airway clearance techniques, and pulmonary rehabilitation programs. The analysis aims to illuminate how these interventions contribute to enhancing respiratory health and overall quality of life. Additionally, this paper briefly outlines its structure, focusing on the evolving landscape of physiotherapeutic strategies. By emphasizing their significance in the comprehensive care paradigm, this review guides individuals navigating the complexities of chronic respiratory diseases towards improved well-being.

Characterising user engagement with mHealth for chronic disease self-management and impact on machine learning performance

Mobile Health (mHealth) has the potential to be transformative in the management of chronic conditions. Machine learning can leverage self-reported data collected with apps to predict periods of increased health risk, alert users, and signpost interventions. Despite this, mHealth must balance the treatment burden of frequent self-reporting and predictive performance and safety. Here we report how user engagement with a widely used and clinically validated mHealth app, myCOPD (designed for the self-management of Chronic Obstructive Pulmonary Disease), directly impacts the performance of a machine learning model predicting an acute worsening of condition (i.e., exacerbations). We classify how users typically engage with myCOPD, finding that 60.3% of users engage frequently, however, less frequent users can show transitional engagement (18.4%), becoming more engaged immediately ( < 21 days) before exacerbating. Machine learning performed better for users who engaged the most, however, this performance decrease can be mostly offset for less frequent users who engage more near exacerbation. We conduct interviews and focus groups with myCOPD users, highlighting digital diaries and disease acuity as key factors for engagement. Users of mHealth can feel overburdened when self-reporting data necessary for predictive modelling and confidence of recognising exacerbations is a significant barrier to accurate self-reported data. We demonstrate that users of mHealth should be encouraged to engage when they notice changes to their condition (rather than clinically defined symptoms) to achieve data that is still predictive for machine learning, while reducing the likelihood of disengagement through desensitisation.

An autonomous wheelchair with health monitoring system based on Internet of Thing

Assistive powered wheelchairs will bring patients and elderly the ability of remain mobile without the direct intervention from caregivers. Vital signs from users can be collected and analyzed remotely to allow better disease prevention and proactive management of health and chronic conditions. This research proposes an autonomous wheelchair prototype system integrated with biophysical sensors based on Internet of Thing (IoT). A powered wheelchair system was developed with three biophysical sensors to collect, transmit and analysis users’ four vital signs to provide real-time feedback to users and clinicians. A user interface software embedded with the cloud artificial intelligence (AI) algorithms was developed for the data visualization and analysis. An improved data compression algorithm Minimalist, Adaptive and Streaming R-bit (O-MAS-R) was proposed to achieve a higher compression ratio with minimum 7.1%, maximum 45.25% compared with MAS algorithm during the data transmission. At the same time, the prototype wheelchair, accompanied with a smart-chair app, assimilates data from the onboard sensors and characteristics features within the surroundings in real-time to achieve the functions including obstruct laser scanning, autonomous localization, and point-to-point route planning and moving within a predefined area. In conclusion, the wheelchair prototype uses AI algorithms and navigation technology to help patients and elderly maintain their independent mobility and monitor their healthcare information in real-time.

Children and exercise.

Exercise is widely understood to improve health outcomes in children and adolescents and to contribute to the prevention and management of many chronic conditions. Australian children are not currently meeting the recommended physical activity guidelines, and these habits are likely to extend into adulthood without intervention. The aim of this paper is to provide generalpractitioners (GPs) with the tools to perform a basic exercise assessment withchildren and adolescents and an understanding of the core principles of exercise prescription for general and special paediatric populations. GPs are limited by time often precluding the assessment of exercise levels in children and adolescents unless it is immediately relevant to their presentation. This article discusses simple methods of assessing physical activity, the importance of appropriately prescribed exercise and its benefits for physical, psychological and social health and wellbeing.

Reciprocal Association Between Chronic Pain and Health Insurance Type in a Population-based Longitudinal Cohort Study

Chronic pain is a widespread condition limiting adults’ daily activities and labor force participation. In the United States, withdrawal from the workforce could be associated with loss of health insurance coverage, while lack of health insurance coverage can limit access to diagnosis and management of chronic health conditions. We used a longitudinal cohort study of middle-aged adults to investigate whether chronic pain is reciprocally associated with coverage by any insurance and type of insurance coverage over a 2-year period (2018 and 2020). Among 5,137 participants (median age of 57 years in 2018), 29% reported chronic pain in either year, while 9 to 10% were uninsured each year. Using multivariable cross-lagged logistic regression analysis, chronic pain in 2018 was not associated with having any insurance coverage in 2020, and lack of coverage in 2018 was not associated with chronic pain in 2020. In further analysis, we determined that public coverage, other (non-private) coverage, or no coverage in 2018 were associated with an increased risk of chronic pain in 2020; while chronic pain in 2018 increased the risk of coverage by public rather than private insurance 2 years later, as well as the risk of coverage by other (non-private) payors. The reciprocal association of non-private insurance coverage and chronic pain may be related to insufficient access to chronic pain treatment among publicly insured adults, or qualification for public insurance based on disability among adults with chronic pain. These results demonstrate that accounting for the type of health insurance coverage is critical when predicting chronic pain in US populations. PerspectiveIn a longitudinal cohort study of middle-aged US adults, the use of public and other non-private insurance predicts future experience of chronic pain, while past experience of chronic pain predicts future use of public and other non-private insurance.

Role of Perceived Social Support in Adherence to Antihypertensives and Controlled Hypertension: Findings of a Community Survey from Urban Nepal.

Social support is considered vital for effective management of chronic conditions, but its role in improving adherence to antihypertensive medication and control of hypertension in urban Nepal is unknown. We examined the role of social support in adherence to antihypertensives and controlled blood pressure to inform future interventions for hypertension management. We analyzed cross-sectional data collected at baseline of a cluster randomized trial of hypertension patients (n=1252) in the community between May and November 2022. Multidimensional scale of perceived social support was used to measure social support, adherence to antihypertensives was measured using the Morisky medication adherence scale -8, and individuals with systolic- and diastolic- blood pressure less than 140 and 90 mmHg respectively were considered to have controlled hypertension. Modified Poisson regression models were used to estimate the prevalence ratios and corresponding 95% confidence intervals. We found that 914 (73%) individuals received moderate to high social support. Participants receiving high social support had a numerically lower proportion of controlled hypertension (51%) however not statistically significant. The proportion of good adherence to antihypertensives did not differ between the social support categories. There was no association in overall, family, friends, and significant other sub-scales of social support with controlled hypertension and adherence to antihypertensives. Further studies to understand the quality and mechanisms through which social support contributes to blood pressure control are needed for the health system to include social support in designing and implementing community-based interventions for hypertension management.

Exploring why individuals utilise naturopathic treatment and choose to combine naturopathy with biomedicine

IntroductionThere has been a global increase in the utilisation of traditional, complementary, and integrative medicine (TCIM), including that of naturopathy. Limited New Zealand research exists that has examined why individuals use naturopathic treatment, and why in some cases, naturopathy is combined with biomedicine. The present study had two main aims: (1) To identify why individuals utilise naturopathic treatment, and (2) to identify why individuals choose to combine naturopathy with biomedicine in the management of chronic health conditions or ongoing symptoms. MethodsParticipants were 20 clients who attended a student naturopathy and herbal medicine teaching clinic in Auckland, New Zealand. Participants were individually interviewed. A structured interview schedule comprising of open-ended questions was used. Data was analysed using an inductive thematic approach. ResultsFive main themes were identified in relation to why individuals utilised naturopathic treatment and combined naturopathy with biomedicine in the management of their chronic health conditions or ongoing symptoms: (1) A holistic approach, (2) a new and different approach, (3) wanting to utilise natural remedies, (4) previous use of naturopathic treatment and/or other forms of TCIM, and (5) word-of-mouth: the role of family and friends in influencing the utilisation of naturopathic treatment. ConclusionsThere was an alignment between what participants desired to seek from naturopathic treatment and the philosophy and core naturopathic treatment principles: a holistic approach to health and healing and the utilisation of natural remedies. Participants combined naturopathic treatment with biomedicine, as it allowed for the use of natural and less invasive ways in treating and managing some of their symptoms. Integration of treatment modalities allowed individuals to retain some control over how their body was treated. Previous use of naturopathy and/or other forms of TCIM influenced current utilisation of naturopathy, either for the same condition or for new condition(s). Family and friends also had a salient role in influencing individuals to seek naturopathic treatment.