Medical Practice Research Articles

A LinkedIn-based analysis of the U.S. dynamic adaptations in healthcare during the COVID-19 pandemic

Despite its side effects on the global environment, the pandemic has created business opportunities for healthcare. This work utilizes LinkedIn data to examine the features of U.S. healthcare companies that operate within a COVID-19 framework. Data from 304 companies in May 2022 and 333 companies in June 2023 from COVID-19-related companies with LinkedIn presence in the U.S. has been collected and analyzed. This study investigates the distinct characteristics of these companies through statistical measures and analysis at the state level. Some of these companies were established long before the pandemic but shifted their orientation toward COVID-19 in response to the crisis, while many others emerged explicitly due to the pandemic. These companies are primarily active in “Health, wellness and fitness,” “Hospital and healthcare,” Nonprofit organization and management,” “Medical practice,” and “Civic and Social organizations.” We show most companies and employees are located in California, and most followers are in the companies in Washington in the first and California in the second data mining.

Automated classification of brain tumor-based magnetic resonance imaging using deep learning approach

The treatment of brain tumors poses significant challenges and contributes to a significant number of deaths on a global scale. The process of identifying brain tumors in medical practice involves the visual analysis of photographs by healthcare experts, who manually delineate the tumor locations. However, this approach is characterized by its time-consuming nature and susceptibility to errors. In recent years, scholars have put forth automated approaches to early detection of brain tumors. However, these techniques face challenges attributed to their limited precision and significant false-positive rates. There is a need for an effective methodology to identify and classify tumors, which involves extracting reliable features and achieving precise disease classification. This work presents a novel model architecture that is derived from the EfficientNetB3. The suggested framework has been trained and assessed on a dataset consisting of 7,023 magnetic resonance images. The findings of this study indicate that the fused feature vector exhibits superior performance compared to the individual vectors. Furthermore, the technique that was provided showed superior performance compared to the currently available systems and attained a 100% accuracy rate. As a result, it is viable to employ this technique within a clinical environment for the purpose of categorizing brain tumors based on magnetic resonance images scans.

AI-powered Neuroprosthetics for brain-computer interfaces (BCIs)

Imagine a world where individuals with lost or impaired sensory or motor function can regain independence and control through technology. This is the promise of neuroprosthetics, a rapidly evolving field that bridges the gap between the nervous system and external devices. Neuroprosthetics encompass a range of implanted or external devices designed to: Substitute for a malfunctioning part of the nervous system. Assist in the recovery or enhancement of lost or impaired function. Augment existing capabilities, creating new possibilities. These devices interact with the nervous system using various methods, including: Electrical stimulation: Directly stimulating nerves or brain tissue to evoke desired responses. Recording brain activity: Capturing electrical signals generated by the brain for further processing and interpretation. Common applications of neuroprosthetics include: Cochlear implants: Restoring hearing in individuals with severe hearing loss. Deep brain stimulation (DBS): Treating movement disorders like Parkinson's disease and essential tremor. Bionic limbs: Providing control of prosthetic arms and legs for individuals with limb loss. Brain-computer interfaces (BCIs): Enabling communication and control of external devices using brain signals alone. Neuroprosthetics offer a glimpse into the future of medicine and technology. With ongoing advancements, these devices have the potential to revolutionize how we treat neurological conditions, restore lost abilities, and even enhance human potential. However, significant challenges remain, including ensuring long-term safety, improving accuracy and reliability, and addressing ethical considerations. As research continues, neuroprosthetics holds immense potential to improve the lives of millions and redefine what it means to be human. The integration of artificial intelligence (AI) with neuroprosthetics has marked a significant milestone in the development of brain-computer interfaces (BCIs). This emerging synergy aims to enhance the quality of life for individuals with disabilities by restoring lost sensory, motor, and cognitive functions. This review article explores the advancements in AI-powered neuroprosthetics for BCIs, focusing on their design, functionality, and the ethical considerations that accompany their integration into medical practice.

Shaping ultrasound in midwifery: towards an evidence-based training framework for enhanced prenatal care.

Academic advancement of the midwifery profession highlights the need to establish standardized qualifications in obstetric ultrasound diagnosis, being a central part of prenatal care. Thus, introduction of an evidence-based training program is warranted. We aimed to reviewed curriculum designs used in midwifery ultrasound education. A systematic literature research was conducted. Embase, PubMed and Google Scholar database was reviewed for publications using the terms "[midwife], [midwives], [midwifery students], [obstetric ultrasound], [midwife sonographer] and [education], [teaching], [program], [course], [curriculum] and [learning]". Papers with full description of curriculum designs or educational programs on obstetrical ultrasound for midwives were included and scrutinized against pre-defined criteria according to the PICO (Population, Intervention, Comparator, Outcomes) scheme. 29 publications were included. Studies demonstrated a significant disparity according to course concepts being used. Differing parameters included: Duration, structure, learning approaches, course content, examination concepts and target groups (practising midwives vs. midwives in education). An evidence-based ultrasound educational program for midwives remains to be developed, including further educational guidelines. Clinical applications by midwives, as well as the distinctions from medical practise, particularly in terms of legal considerations, needs to be defined.

Tissue Ablation: Applications and Perspectives.

Tissue ablation techniques have emerged as a critical component of modern medical practice and biomedical research, offering versatile solutions for treating various diseases and disorders. Percutaneous ablation is minimally invasive and offers numerous advantages over traditional surgery, such as shorter recovery times, reduced hospital stays, and decreased healthcare costs. Intra-procedural imaging during ablation also allows precise visualization of the treated tissue volume while minimizing injury to surrounding normal tissues, reducing the risk of complications. Here, we explore the mechanisms of tissue ablation and innovative energy delivery systems, highlighting recent advancements that have reshaped the landscape of clinical practice. We will also discuss current clinical challenges related to tissue ablation, underlining unmet clinical needs for more advanced material-based approaches to improve the delivery of energy and pharmacology-based therapeutics. This article is protected by copyright. All rights reserved.

IMPLEMENTING ADVANCED X-RAY TECHNOLOGIES AT THE THIRD CHERKASY CITY EMERGENCY HOSPITAL

Introduction: In recent decades, the world has seen a transition from traditional to digital radiography. Ukraine has also joined this process, replacing outdated equipment with modern digital systems that have become especially important during the Covid-19 epidemic and the Russian-Ukrainian war. The Third Cherkasy City Emergency Hospital implements modern digital technologies of X-ray diagnostics in order to improve the provision of medical care and diagnostics. This study aims at investigating and evaluating the experience of implementing digital X-ray technologies in The Third Cherkasy City Emergency Hospital. Materials and methods: This study involved analyzing medical records from The Third Cherkasy City Emergency Hospital and conducting individual interviews with eight healthcare professionals, including radiologists, other physicians, and a nurse from the hospital. Results. Beginning in 2017, due to the decentralization policy and changes in the Cherkassy city administration, there has been a gradual transition of the medical sector, particularly The Third Cherkassy City Emergency Hospital, to modern digital equipment. This transition has significantly enhanced the quality of medical services and streamlined the process of diagnosing and treating patients. The integration of digital X-ray technologies into the hospital's medical practice has expedited the acquisition and processing of X-ray images, reducing labor and time previously spent on film installation and processing. This reduction in personnel and equipment needs has led to cost savings and process optimization. The implementation of modern X-ray technology has notably improved the efficiency and workflow of hospital staff, facilitating faster and more accurate processing and analysis of X-ray images. The absence of chemical reagents and the utilization of high-quality, clear images have reduced physical and emotional stress among medical personnel. Furthermore, the technology has enabled more effective detection of various diseases at early stages and streamlined emergency care for injured patients. Additionally, the impact of X-ray radiation on both patients and medical staff has decreased. However, the adoption of digital technologies has brought forth new challenges, such as organizing storage and access to digital archives. Addressing these challenges necessitates additional investments in server equipment and the development of specialized programs. Ensuring the reliability and security of medical information storage is crucial to prevent potential data loss or corruption.

The quality of reporting in case reports of permanent neonatal diabetes mellitus: a cross-sectional study

BackgroundAlthough randomized trials and systematic reviews provide the best evidence to guide medical practice, many permanent neonatal diabetes mellitus (PNDM) studies have been published as case reports. However, the quality of these studies has not been assessed. The purpose of this study was to assess the extent to which the current case reports for PNDM comply with the Case Report (CARE) guidelines and to explore variables associated with the reporting.MethodSix English and four Chinese databases were searched from their inception to December 2022 for PNDM case reports. The 23 items CARE checklist was used to measure reporting quality. Primary outcome was the adherence rate of each CARE item and second outcome was total reporting score for each included PNDM case report. Linear and logistic regression analyses were used to examine the connection between five pre-specified predictor variables and the reporting quality. The predictor variables were impact factor of the published journal (<3.4 vs. ≥3.4, categorized according to the median), funding (yes vs. no), language (English vs. other language), published journal type (general vs. special) and year of publication (>2013 vs. ≤ 2013).ResultIn total, 105 PNDM case reports were included in this study. None of the 105 PNDM case reports fulfilled all 23 items of the CARE checklist. The response rate of 11 items were under 50%, including prognostic characteristics presentation (0%), patient perspective interpretation (0%), diagnostic challenges statement (2.9%), clinical course summary (21.0%), diagnostic reasoning statement (22.9%), title identification (24.8%), case presentation (33.3%), disease history description (34.3%), strengths and limitations explanation (41.0%), informed consent statement (45.7%), and lesson elucidation (47.6%). This study identified that the PNDM case reports published in higher impact factor journals were statistically associated with a higher reporting quality.ConclusionThe reporting of case reports for PNDM is generally poor. As a result, this information may be misleading to providers, and the clinical applications may be detrimental to patient care. To improve reporting quality, journals should encourage strict adherence to the CARE guidelines.

Bioethics, Suffering, and the Culture Wars

This article provides an analysis of the enduring disagreements among bioethicists over the divide between secular and religious boundaries that are reflected in liberal, libertarian, and conservative approaches to medicine as a profession and vocation. At the beginning of the twentieth century, the most authoritative voices to address the problem of suffering were Protestants, Strict Calvinists, hydropaths, and homeopaths. Other religious and medical groups had regularly confronted pain and suffering in the nineteenth century in light of the discovery and increasing use of anesthesia. Rationalizations for suffering were first and foremost indebted to strong beliefs about divine will and about the seemingly inevitable course of nature. Did physical pain reflect the wrongdoing of one individual or of an entire community? What was the appropriate way to respond to the natural circumstances of growth, decay, and healing? Such questions produced a varied rhetoric of suffering that emerged in new ways in the second half of the twentieth century. Questions and concerns about the ethical foundations of medical practice—what should and should not be permitted—illustrate the present cultural struggles.

Evaluating ChatGPT's effectiveness and tendencies in Japanese internal medicine.

ChatGPT, a large-scale language model, is a notable example of AI's potential in health care. However, its effectiveness in clinical settings, especially when compared to human physicians, is not fully understood. This study evaluates ChatGPT's capabilities and limitations in answering questions for Japanese internal medicine specialists, aiming to clarify its accuracy and tendencies in both correct and incorrect responses. We utilized ChatGPT's answers on four sets of self-training questions for internal medicine specialists in Japan from 2020 to 2023. We ran three trials for each set to evaluate its overall accuracy and performance on nonimage questions. Subsequently, we categorized the questions into two groups: those ChatGPT consistently answered correctly (Confirmed Correct Answer, CCA) and those it consistently answered incorrectly (Confirmed Incorrect Answer, CIA). For these groups, we calculated the average accuracy rates and 95% confidence intervals based on the actual performance of internal medicine physicians on each question and analyzed the statistical significance between the two groups. This process was then similarly applied to the subset of nonimage CCA and CIA questions. ChatGPT's overall accuracy rate was 59.05%, increasing to 65.76% for nonimage questions. 24.87% of the questions had answers that varied between correct and incorrect in the three trials. Despite surpassing the passing threshold for nonimage questions, ChatGPT's accuracy was lower than that of human specialists. There was a significant variance in accuracy between CCA and CIA groups, with ChatGPT mirroring human physician patterns in responding to different question types. This study underscores ChatGPT's potential utility and limitations in internal medicine. While effective in some aspects, its dependence on question type and context suggests that it should supplement, not replace, professional medical judgment. Further research is needed to integrate Artificial Intelligence tools like ChatGPT more effectively into specialized medical practices.

Человек - мессия

This lecture is dedicated to the messianic activity of Louis Pasteur, one of the most outstanding figures in humane and veterinary medicine, the founder of microbiology and immunology, who made the most significant fundamental contribution to the scientific solution of microbiological problems of global significance. Together with his colleagues and followers, he was the first to establish the role of microbes in life on Earth, including in pathology, the bacterial etiology of infectious diseases and the universal nature of anti-infective immunity, discovered the phenomenon of artificially attenuation the pathogenic properties of infectious agents and created means and methods of protection against the most malignant diseases of animals and humans - vaccines against anthrax and rabies, immediately, even during his lifetime, which found wide application in veterinary and medical practice around the world with outstanding socio-economic efficiency.

Publication Trends and Hot Spots of ChatGPT's Application in the Medicine.

This study aimed to analyze the current landscape of ChatGPT application in the medical field, assessing the current collaboration patterns and research topic hotspots to understand the impact and trends. By conducting a search in the Web of Science, we collected literature related to the applications of ChatGPT in medicine, covering the period from January 1, 2000 up to January 16, 2024. Bibliometric analyses were performed using CiteSpace (V6.2., Drexel University, PA, USA) and Microsoft Excel (Microsoft Corp.,WA, USA) to map the collaboration among countries/regions, the distribution of institutions and authors, and clustering of keywords. A total of 574 eligible articles were included, with 97.74% published in 2023. These articles span various disciplines, particularly in Health Care Sciences Services, with extensive international collaboration involving 73 countries. In terms of countries/regions studied, USA, India, and China led in the number of publications. USA ot only published nearly half of the total number of papers but also exhibits a highest collaborative capability. Regarding the co-occurrence of institutions and scholars, the National University of Singapore and Harvard University held significant influence in the cooperation network, with the top three authors in terms of publications being Wiwanitkit V (10 articles), Seth I (9 articles), Klang E (7 articles), and Kleebayoon A (7 articles). Through keyword clustering, the study identified 9 research theme clusters, among which "digital health"was not only the largest in scale but also had the most citations. The study highlights ChatGPT's cross-disciplinary nature and collaborative research in medicine, showcasing its growth potential, particularly in digital health and clinical decision support. Future exploration should examine the socio-economic and cultural impacts of this trend, along with ChatGPT's specific technical uses in medical practice.

Diagnosis of post-traumatic syndrome: functional-vegetative analysis of sensory systems

Background. The article analyzes the relationship between emotional states and the psycho-vegetative status of the respondents using functional-vegetative diagnosis, which is important for medical practice. The study was based on the use of functional-vegetative diagnosis, including the analysis of the parameters of the autonomic nervous system, cardiovascular reactivity and other indicators characterizing the psycho-vegetative status of the individual. The purpose: to justify the functional-vegetative diagnosis of sensory systems in the context of the organization of the psychological health of the individual. Materials and methods. The following theoretical methods were used: comparison of existing psychophysiological concepts, structural and genetic analysis of sensory systems, synthesis of theoretical and methodological approaches of the fields of psychophysiology, inductive-deductive approach to the study of the problem. Empirical methods include: measurements according to the functional-vegetative method of V. Makats on the comparison by quantitative signs of the dynamics of each participant in the experiment and comparison of the relative optimal coefficient of vegetative balance and integrated generalization of data in groups with the same initial level of vegetative balance and surveys to determine emotional psychological background on the Izard’s Differential Emotions Scale, according to the results of which an increase in positive emotions and preservation of a moderate level of positive dynamics due to the influence of a psycho-emotional stimulus was recorded. Conclusions. It is noted that the influence of the psycho-emotional factor is a rehabilitation aspect that has a normalizing effect on the sympathetic and parasympathetic nervous systems and functional-vegetative homeostasis. The obtained results open perspectives for further research on diagnosis and correction of mental and physical health.

ESTIMATION OF THE POSTMORTEM INTERVAL BY CRANIOENCEPHALIC THERMOMETRY WITH A SINGLE DISCRETE DECREASE IN AMBIENT TEMPERATURE

Aim– development of a method implemented in the format of a computer program for determining the postmortem interval (PMI) by cranioencephalic temperature (CT) of a corpse under conditions of cooling with a single discrete decrease in ambient temperature. Material and methods. Analytical and finite element modeling of CT dynamics with a single discrete decrease in ambient temperature is performed. Results. A mathematical model has been developed for determining the PMI and the uncertainty of its estimates with a single discrete decrease in the ambient temperature. The values of the constants of the model equation and their variances are determined on the basis of finite element modeling of CT dynamics under the specified cooling conditions. The computational algorithm of the specified method for determining PMI and contraindications to its use are implemented in the C# language in the form of the Warm Bodies DSC program. Conclusion. The developed method and the application implementing it are recommended for use in forensic medical practice to determine the PMI with a single discrete decrease in ambient temperature.

Diagnostic errors in rheumatology and medico-legal consequences.

Medical errors and adverse effects of treatment are inherent to medical practice. Like any other medical specialty, rheumatology is not exempt. Although the problem is imprecisely quantified, according to some authors it affects up to 10% of hospitalised patients. Describing and qualifying misdiagnoses in rheumatology will help us to understand and reduce these. Further, misdiagnosis generates unjustified costs and medico-legal consequences with errors in initial diagnosis the basis for medico-legal disputes involving assessment of work incapacity.

Anxiety in the emergency medical practice – its psychiatric and somatic origin, comorbidities, behavior and treatment

Anxiety conditions and disorders are common in the general population, and patients suffering from them often seek the services of emergency departments. Anxiety is a psychopathological symptom that accompanies not only psychiatric conditions, but a wide range of somatic diseases, and a combination of both. The biochemical and pathophysiological mechanisms of psychosomatic interrelationship and comorbidity are complex and multi-layered. Thus, diagnosing the root cause of anxiety is a clinical challenge. Early, and on time, recognition of an anxiety disorder helps to avoid unnecessary investigations, ensures correct treatment and saves hospital resources. Careful use of medications, psychoeducation and referral to a specialist improves patient outcome with this potentially debilitating disease. In this article, the authors aim to present in a synthesized form the main epidemiological data on the prevalence of anxiety symptoms and disorders, anatomical localization and biochemical mechanisms and relationships in the pathogenesis of anxiety symptoms, as well as to derive the main guidelines for recognizing and differentiating clinicopathological constellations in somatic conditions in emergency medical practice. Materials and methods. Existing published studies from an international database, related to the subject of the article, have been thoroughly studied. Results. Anxiety symptoms, in particular panic attacks and disorders, are widespread in primary care and occupy a significant part of the work process, especially at times of peak loads, natural disasters and situations of mass traumatism. Conclusions. Timely training and good preparation for recognition and adequate assessment of anxiety conditions in primary and emergency medical care significantly shorten the therapeutic route of patients. They receive competent help on time, and the cost of their treatment is significantly reduced. Discussion. Modern medical science, including psychiatric, offers advanced drug and non-drug methods for the treatment and prevention of anxiety conditions and disorders.

Understanding the root of healing and beyond: Exploring the way forward for Alternative Medicine in Nigeria

Complementary and alternative medicine involves medical practices rooted in traditional methods such as herbal remedies and spiritual beliefs. Historical factors influence the practice of alternative medicine in Nigeria. This study examines cultural perceptions, practices, challenges, and integration strategies for alternative medicine in the Nigerian healthcare system. Nigeria, with a population of over 200 million, faces significant health challenges, necessitating robust healthcare systems. Despite having over 80,000 registered doctors, there is a low doctor-to-population ratio of 4,000 to 5,000 people per doctor. Traditional healers practicing under partial regulation significantly contribute to healthcare delivery by using indigenous herbal and spiritual therapies. Challenges in integrating alternative medicine include standardization, limited scientific evidence, stigma, funding constraints, and barriers to access of services . Integration efforts involve creating inclusive healthcare systems that combine traditional and modern approaches, prioritize equitable access, and respect for cultural diversity, developing standardized training, generating scientific evidence, and increasing public awareness. Collaboration among stakeholders, such as healers, healthcare providers, policymakers, researchers, and communities, is essential for successful integration and improved healthcare outcomes. The Nigerian healthcare system can benefit from integrating alternative medicine and promoting holistic and culturally sensitive practices. Overcoming these challenges requires cooperation, evidence-based strategies, and investments in research, leading to more effective healthcare delivery, improved health outcomes, and reduced disparities nationwide. Countries on integration journeys should prioritize collaboration, establish clear regulations, raise public awareness, and invest in research to support the effectiveness and safety of alternative medicine.

Geographic Accessibility of General Practitioners by Car and Public Transport - A Study Using the Minimum Travel Time Method in a Rural Area in the North-East of Germany

Basic medical care should be accessible to all people without restriction. However, the distribution of practices in rural areas is often limited to the centers, meaning that distances have to be covered. The Federal Joint Committee (G-BA), the highest decision-making body of the joint self-government of physicians, dentists, hospitals and health insurance funds in Germany, only states for cars that 95% of the population should be able to reach general practitioners (GPs) in less than 20 minutes on average. The aim of this study was to determine the geographic accessibility of GP practices by car and public transport. A cross-sectional study was conducted in a rural area in the north-east of Germany called Neustrelitz Central Zone and reported according to the STROBE statement. Geographic data of OpenStreetMap and the Federal Agency for Cartography and Geodesy and GP practices data of the Associations of Statutory Health Insurance Physicians Mecklenburg-Western Pomerania and Brandenburg were used. Based on the method of minimum travel time, the required travel times by car and public transport from the local centers to the three nearest physician locations were determined using various online tools. On average, inhabitants need 10.7 minutes to reach the three nearest GP practices by car, up to a maximum of 19 minutes. The average travel time by public transport for an appointment at 10 a.m. is four hours and twelve minutes. While it is possible for all municipalities (and their inhabitants) to reach the nearest GP practices in time for an appointment at 10 a.m. and to complete the return journey on the same day, this is no longer possible for 35% of municipalities (and their inhabitants) for an appointment at 3 p.m. and for 53% for an appointment at 5 p.m. In the Neustrelitz Central Zone, the accessibility of GP practices by car is ensured in accordance with the G-BA statements. On the other hand, the accessibility of GP practices by public transport can be a problem for people who do not have their own car. This could be remedied, for example, by expanding eHealth or mobile medical practices.

A SURVEY ON CONTINUOUS POSTGRADUATE DISASTER MEDICINE EDUCATION NEEDS IN THE PLOVDIV REGION

Introduction: Disasters, regardless of their origin, have a direct negative impact on the physical and psychological wellbeing of the population. Medical support for the casualties necessitates specific organization and training of medical personnel. Knowledge and skills in the field are considered to be essential for the execution of a rapid response. Purpose: The aim of this research was to study the need for postgraduate disaster medicine education for different categories of medical professionals in the Plovdiv region. Materials and methods: A cross-sectional study was conducted in 2020 through an anonymous inquiry among medical professionals from pre-hospital healthcare, hospital care and the centers for emergency medical aid in the Plovdiv region. Results: The survey was held among 160 medical professionals. They were interviewed regarding their participation in medical support for disasters or mass casualty incidents. 50,3% of them had such experience. 65% of the respondents evaluated their knowledge of disaster medicine as moderate, while only 18,7% reported high self-assessment. Most interviewees knew the knowledge and skills needed for disaster medical support, but half had never trained in these skills. Almost all respondents - 93,1%, considered disaster medicine knowledge useful for medical practice. 89,4% share the opinion that postgraduate courses were necessary. 93,2% preferred to be trained and educated on the subject by the Medical University. Conclusions: The results from our survey highlight the lower than expected self-confidence among medical professionals regarding their disaster medical support knowledge and skills. Postgraduate training could improve disaster resilience by increasing skill and confidence.

An Innovative Approach on Yao’s Three-Way Decision Model Using Intuitionistic Fuzzy Sets for Medical Diagnosis

In the realm of medical diagnosis, intuitionistic fuzzy data serves as a valuable tool for representing information that is uncertain and imprecise. Nevertheless, decision-making based on this kind of knowledge can be quite challenging due to the inherent vagueness of the data. To address this issue, we employ power aggregation operators, which prove effective in combining several sources of data, such as expert thoughts and patient information. This allows for a more correct diagnosis; a particularly crucial aspect of medical practice where precise and timely diagnoses can significantly impact medication policy and patient results. In our research, we introduce a novel methodology to the three-way decision idea. Initially, we revamp the three-way decision model using rough set theory and incorporate interval-valued classes to handle intuitionistic fuzzy data. Secondly, we explore the use of intuitionistic fuzzy power weighted and intuitionistic fuzzy power weighted geometric aggregation operators to consolidate attribute values within the data system. Furthermore, we present a case study in the medical field to exhibit the validity and efficiency of our offered technique. This innovative method enables us to classify participants into three distinct zones based on their symptoms. The manuscript concludes with a summary of key points provided by the authors.

Evaluation of lived experience Peer Support intervention for mental health service consumers in Primary Care (PS-PC): study protocol for a stepped-wedge cluster randomised controlled trial

BackgroundThe demand for mental health services in Australia is substantial and has grown beyond the capacity of the current workforce. As a result, it is currently difficult for many to access secondary healthcare providers. Within the secondary healthcare sector, however, peer workers who have lived experience of managing mental health conditions have been increasingly employed to intentionally use their journey of recovery in supporting others living with mental health conditions and their communities. Currently, the presence of peer workers in primary care has been limited, despite the potential benefits of providing supports in conjunction with GPs and secondary healthcare providers.MethodsThis stepped-wedge cluster randomised controlled trial (RCT) aims to evaluate a lived experience peer support intervention for accessing mental health care in primary care (PS-PC). Four medical practices across Australia will be randomly allocated to switch from control to intervention, until all practices are delivering the PS-PC intervention. The study will enrol 66 patients at each practice (total sample size of 264). Over a period of 3–4 months, 12 h of practical and emotional support provided by lived experience peer workers will be available to participants. Scale-based questionnaires will inform intervention efficacy in terms of mental health outcomes (e.g., self-efficacy) and other health outcomes (e.g., healthcare-related costs) over four time points. Other perspectives will be explored through scales completed by approximately 150 family members or carers (carer burden) and 16 peer workers (self-efficacy) pre- and post-intervention, and 20 medical practice staff members (attitudes toward peer workers) at the end of each study site’s involvement in the intervention. Interviews (n = 60) and six focus groups held toward the end of each study site’s involvement will further explore the views of participants, family members or carers, peer workers, and practice staff to better understand the efficacy and acceptability of the intervention.DiscussionThis mixed-methods, multi-centre, stepped-wedge controlled study will be the first to evaluate the implementation of peer workers in the primary care mental health care sector.Trial registrationAustralian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12623001189617. Registered on 17 November 2023, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=386715