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Women's health care has evolved significantly since it was first acknowledged as an integral part of internal medicine training more than two decades ago. To update and clarify core competencies in sex- and gender-based women's health for general internists, the Society of General Internal Medicine (SGIM) Women and Medicine Commission prepared the following Position Paper, approved by the SGIM council in 2023. Competencies were developed using several sources, including the 2021 Accreditation Council for Graduate Medical Education Program Requirements for Internal Medicine and the 2023 American Board of Internal Medicine Certification Examination Blueprint. These competencies are relevant to the care of patients who identify as women, as well as gender-diverse individuals to whom these principles apply. They align with pivotal advances in women's health and acknowledge the changing context of patients' lives, reaffirming the role of general internal medicine physicians in providing comprehensive care to women.

As part of an investment by the Bill & Melinda Gates Foundation to support the Government of Bihar to improve reproductive, maternal, newborn and child health and nutrition (RMNCHN) statewide, BBC Media Action implemented multiple communication tools to support front-line worker (FLW) outreach. We analyse the impacts of a package of mHealth audio messaging and paper-based job aids used by FLWs during government-sponsored village health, sanitation and nutrition days (VHSNDs) on knowledge and practices of childbearing women across the RMNCHN continuum of care. Data from two surveys collected between July and September 2016 were analysed using logistic regression to compare health-related knowledge and behaviours between women who had been exposed at VHSNDs to the mHealth GupShup Potli (GSP) audio recordings or interpersonal communication (IPC) tools versus those who were unexposed. Exposure to GSP recordings (n=2608) was associated with improved knowledge across all continuum-of-care domains, as well as improved health-related behaviours in some domains. The odds of having taken iron-folic acid (IFA) tablets were significantly higher in exposed women (OR 1.5, 95% CI 1.1 to 2.2), as was contraceptive use (OR 2.0, 95% CI 1.2 to 3.2). There were no differences in birth preparedness or complementary feeding practices between groups. Exposure to IPC paper-based tools (n=2002) was associated with a twofold increased odds of IFA consumption (OR 2.3, 95% CI 1.7 to 3.2) and contraceptive use (OR 1.8, 95% CI 1.2 to 2.8). Women exposed to both tools were generally at least twice as likely to subsequently discuss the messages with others. BBC Media Action's mHealth audio messaging job aids and paper-based IPC tools were associated with improved knowledge and practices of women who were exposed to them across multiple domains, suggesting their important potential for improving health outcomes for beneficiaries at scale in low-resource settings. NCT02726230.

BackgroundBrucellosis, as a serious zoonotic infectious disease, has been recognized as a re-emerging disease in the developing countries worldwide. In china, the incidence of brucellosis is increasing each year, seriously threatening the health of humans as well as animal populations. Despite a quite number of diagnostic methods currently being used for brucellosis, innovative technologies are still needed for its rapid and accurate diagnosis, especially in area where traditional diagnostic is unavailable.Methodology/principal findingsIn this study, a total of 22 B cell linear epitopes were predicted from five Brucella outer membrane proteins (OMPs) using an immunoinformatic approach. These epitopes were then chemically synthesized, and with the method of indirect ELISA (iELISA), each of them displayed a certain degree of capability in identifying human brucellosis positive sera. Subsequently, a fusion protein consisting of the 22 predicted epitopes was prokaryotically expressed and used as diagnostic antigen in a newly established brucellosis testing method, nano-ZnO modified paper-based ELISA (nano-p-ELISA). According to the verifying test using a collection of sera collected from brucellosis and non-brucellosis patients, the sensitivity and specificity of multiepitope based nano-p-ELISA were 92.38% and 98.35% respectively. The positive predictive value was 98.26% and the negative predictive value was 91.67%. The multiepitope based fusion protein also displayed significantly higher specificity than Brucella lipopolysaccharide (LPS) antigen.ConclusionsB cell epitopes are important candidates for serologically testing brucellosis. Multiepitope fusion protein based nano-p-ELISA displayed significantly sensitivity and specificity compared to Brucella LPS antigen. The strategy applied in this study will be helpful to develop rapid and accurate diagnostic method for brucellosis in human as well as animal populations.

UnlabelledThis position paper reviews how the National Bone Health Alliance (NBHA) will execute a project to help assure health professionals of the clinical utility of bone turnover markers; the current clinical approaches concerning osteoporosis and the status and use of bone turnover markers in the USA; the rationale for focusing this effort around two specific bone turnover markers; the need to standardize bone marker sample collection procedures, reference ranges, and bone turnover marker assays in clinical laboratories; and the importance of harmonization for future research of bone turnover markers.IntroductionOsteoporosis is a major global health problem, with the prevalence and incidence of osteoporosis for at-risk populations estimated to be 44 million Americans. The potential of bone markers as an additional tool for health care professionals to improve patient outcomes and impact morbidity and mortality is crucial in providing better health care and addressing rising health care costs. This need to advance the field of bone turnover markers has been recognized by a number of organizations, including the International Osteoporosis Foundation (IOF), National Osteoporosis Foundation, International Federation of Clinical Chemistry, and Laboratory Medicine (IFCC), and the NBHA.MethodsThis position paper elucidates how this project will standardize bone turnover marker sample collection procedures in the USA, establish a USA reference range for one bone formation (serum procollagen type I N propeptide, s-PINP) and one bone resorption (serum C-terminal telopeptide of type I collagen, s-CTX) marker, and standardize bone turnover marker assays used in clinical laboratories. This effort will allow clinicians from the USA to have confidence in their use of bone turnover markers to help monitor osteoporosis treatment and assess future fracture risk. This project builds on the recommendations of the IOF/IFCC Bone Marker Standards Working Group by developing USA reference standards for s-PINP and s-CTX, the markers identified as most promising for use as reference markers.ResultsThe goals of this project will be realized through the NBHA and will include its governmental, academic, for-profit, and non-profit sector stakeholders as well as major academic and commercial laboratories. Upon completion, a parallel effort will be pursued to make bone turnover marker measurements reliable and accepted by all health care professionals for facilitating treatment decisions and ultimately be reimbursed by all health insurance payers.ConclusionsSuccessful completion of this project will help assure health professionals from the USA of the clinical utility of bone turnover markers and ties in with the parallel effort of the IOF/IFCC to develop worldwide bone turnover reference ranges.

Engagement is an important component in the advancement of gene-drive vector control research programs as developers look to transition the technology from the laboratory to the field. As research advances and engagement surrounding this novel technology is put into practice, knowledge can be gained from practical experiences and applications in the field. A relationship-based model (RBM) provides a framework for end-user development of engagement programs and strategies. The model places end users at the center of the engagement decision-making processes rather than as recipients of predetermined strategies, methods, and definitions. Successful RBM application for healthcare delivery has previously been demonstrated, and the University of California Malaria Initiative (UCMI) has applied this model to its gene-drive program in the Democratic Republic of São Tomé and Príncipe. The model emphasizes the importance of local leadership in the planning, development, and implementation of all phases of project engagement. The primary aim of this paper is to translate the model from paper to practice and provide a transparent description, using practical examples, of the UCMI program implementation of RBM at its field site. End-user development of the UCMI engagement program provides a unique approach to the development of ethical, transparent, and effective engagement strategies for malaria control programs. This paper may also serve as a reference and example for projects looking to establish an engagement program model that integrates end-user groups in the decision-making processes surrounding engagement.

In 2019, the National Health Interview survey found that nearly 59% of adults reported pain some, most, or every day in the past 3 months, with 39% reporting back pain, making back pain the most prevalent source of pain, and a significant issue among adults. Often, identifying a direct, treatable cause for back pain is challenging, especially as it is often attributed to complex, multifaceted issues involving biological, psychological, and social components. Due to the difficulty in treating the true cause of chronic low back pain (cLBP), an over-reliance on opioid pain medications among cLBP patients has developed, which is associated with increased prevalence of opioid use disorder and increased risk of death. To combat the rise of opioid-related deaths, the National Institutes of Health (NIH) initiated the Helping to End Addiction Long-TermSM (HEAL) initiative, whose goal is to address the causes and treatment of opioid use disorder while also seeking to better understand, diagnose, and treat chronic pain. The NIH Back Pain Consortium (BACPAC) Research Program, a network of 14 funded entities, was launched as a part of the HEAL initiative to help address limitations surrounding the diagnosis and treatment of cLBP. This paper provides an overview of the BACPAC research program's goals and overall structure, and describes the harmonization efforts across the consortium, define its research agenda, and develop a collaborative project which utilizes the strengths of the network. The purpose of this paper is to serve as a blueprint for other consortia tasked with the advancement of pain related science.

Bipolar disorder is heterogeneous in phenomenology, illness trajectory, and response to treatment. Despite evidence for the efficacy of multimodal-ity interventions, the majority of persons affected by this disorder do not achieve and sustain full syndromal recovery. It is eagerly anticipated that combining datasets across various information sources (e.g., hierarchical "multi-omic" measures, electronic health records), analyzed using advanced computational methods (e.g., machine learning), will inform future diagnosis and treatment selection. In the interim, identifying clinically meaningful subgroups of persons with the disorder having differential response to specific treatments at point-of-care is an empirical priority. This paper endeavours to synthesize salient domains in the clinical characterization of the adult patient with bipolar disorder, with the overarching aim to improve health outcomes by informing patient management and treatment considerations. Extant data indicate that characterizing select domains in bipolar disorder provides actionable information and guides shared decision making. For example, it is robustly established that the presence of mixed features - especially during depressive episodes - and of physical and psychiatric comorbidities informs illness trajectory, response to treatment, and suicide risk. In addition, early environmental exposures (e.g., sexual and physical abuse, emotional neglect) are highly associated with more complicated illness presentations, inviting the need for developmentally-oriented and integrated treatment approaches. There have been significant advances in validating subtypes of bipolar disorder (e.g., bipolar I vs. II disorder), particularly in regard to pharmacological interventions. As with other severe mental disorders, social functioning, interpersonal/family relationships and internalized stigma are domains highly relevant to relapse risk, health outcomes, and quality of life. The elevated standardized mortality ratio for completed suicide and suicidal behaviour in bipolar disorder invites the need for characterization of this domain in all patients. The framework of this paper is to describe all the above salient domains, providing a synthesis of extant literature and recommendations for decision support tools and clinical metrics that can be implemented at point-of-care.

Maternity services cannot be postponed due to the nature of this service, however, the pandemic resulted in wide-ranging and significant changes to working practices and services. This paper aims to describe UK midwives' experiences of working during the COVID-19 pandemic. This study forms part of a larger multiple phase research project using a cross-sectional design based on an online survey. The online survey used validated psychometric tools to measure work-related quality of life, wellbeing, coping, and burnout as well as open-ended questions to further understand the experiences of staff working during the pandemic. This paper reports the qualitative data collected from the open-ended questions. The qualitative data were subjected to thematic analysis and the four main themes that emerged were 'relentless stress/pressure', 'reconfiguration of services', 'protection of self and others', and 'workforce challenges'. The key conclusions were that midwives experienced a reduction in quality of working life and significant stress throughout the pandemic due to a range of factors including staffing shortages, restrictions placed on women's partners, changes to services and management support, all of which compounded workforce pressures that existed prior to the pandemic. This research recommends consultation of front-line midwives in relation to possible changes in practice and workforce planning in preparation for crises such as a pandemic and to ensure equitable and supportive management with access to practical and psychological support.

BackgroundIn Peru, a majority of individuals bypass primary care facilities even for routine services. Efforts to strengthen primary care must be informed by understanding of current practice. We conducted a time motion assessment in primary care facilities in Lima with the goals of assessing the feasibility of this method in an urban health care setting in Latin America and of providing policy makers with empirical evidence on the use of health care provider time in primary care.MethodsThis cross-sectional continuous observation time motion study took place from July - September 2019. We used two-stage sampling to draw a sample of shifts for doctors, nurses, and midwives in primary health facilities and applied the Work Observation Method by Activity Timing tool to capture type and duration of provider activities over a 6-h shift. We summarized time spent on patient care, paper and electronic record-keeping, and non-work (personal and inactive) activities across provider cadres. Observations are weighted by inverse probability of selection.ResultsTwo hundred seventy-five providers were sampled from 60 facilities; 20% could not be observed due to provider absence (2% schedule error, 8% schedule change, 10% failure to appear). One hundred seventy-four of the 220 identified providers consented (79.1%) and were observed for a total of 898 h of provider time comprising 30,312 unique tasks. Outpatient shifts included substantial time on patient interaction (110, 82, and 130 min for doctors, nurses, and midwives respectively) and on paper records (132, 97, and 141 min) on average. Across all shifts, 1 in 6 h was spent inactive or on personal activities. Two thirds of midwives used computers compared to half of nurses and one third of doctors.ConclusionsThe time motion study is a feasible method to capture primary care operations in Latin American countries and inform health system strengthening. In the case of Lima, absenteeism undermines health worker availability in primary care facilities, and inactive time further erodes health workforce availability. Productive time is divided between patient-facing activities and a substantial burden of paper-based record keeping for clinical and administrative purposes. Electronic health records remain incompletely integrated within routine care, particularly beyond midwifery.

Biosocial Medicine, with its emphasis on the full integration of the person's biology and biography, proposes a strategy for clinical research and the practice of medicine that is transformative for the care of individual patients. In this paper, we argue that Biology is one component of what makes a person unique, but it does not do so alone. Biography, the lived experience of the person, integrates with biology to create a unique signature for each individual and is the foundational concept on which Biosocial Medicine is based. Biosocial Medicine starts with the premise that the individual patient is the focus of clinical care, and that average results for "ideal" patients in population level research cannot substitute for the "real" patient for whom clinical decisions are needed. The paper begins with a description of the case-based method of clinical reasoning, considers the strengths and limitations of Randomized Controlled Trials and Evidence Based Medicine, reviews the increasing focus on precision medicine and then explores the neglected role of biography as part of a new approach to the tailored care of patients. After a review of the analytical challenges in Biosocial Medicine, the paper concludes by linking the physician's commitment to understanding the patient's biography as a critical element in developing trust with the patient.

Patient-reported outcomes (PROs) are used in clinical trials to provide valuable evidence on the impact of disease and treatment on patients' symptoms, function and quality of life. High-quality PRO data from trials can inform shared decision-making, regulatory and economic analyses and health policy. Recent evidence suggests the PRO content of past trial protocols was often incomplete or unclear, leading to research waste. To address this issue, international, consensus-based, PRO-specific guidelines were developed: the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT)-PRO Extension. The SPIRIT-PRO Extension is a 16-item checklist which aims to improve the content and quality of aspects of clinical trial protocols relating to PRO data collection to minimise research waste, and ultimately better inform patient-centred care. This SPIRIT-PRO explanation and elaboration (E&E) paper provides information to promote understanding and facilitate uptake of the recommended checklist items, including a comprehensive protocol template. For each SPIRIT-PRO item, we provide a detailed description, one or more examples from existing trial protocols and supporting empirical evidence of the item's importance. We recommend this paper and protocol template be used alongside the SPIRIT 2013 and SPIRIT-PRO Extension paper to optimise the transparent development and review of trial protocols with PROs.

Generative Artificial Intelligence is set to revolutionize healthcare delivery by transforming traditional patient care into a more personalized, efficient, and proactive process. Chatbots, serving as interactive conversational models, will probably drive this patient-centered transformation in healthcare. Through the provision of various services, including diagnosis, personalized lifestyle recommendations, dynamic scheduling of follow-ups, and mental health support, the objective is to substantially augment patient health outcomes, all the while mitigating the workload burden on healthcare providers. The life-critical nature of healthcare applications necessitates establishing a unified and comprehensive set of evaluation metrics for conversational models. Existing evaluation metrics proposed for various generic large language models (LLMs) demonstrate a lack of comprehension regarding medical and health concepts and their significance in promoting patients’ well-being. Moreover, these metrics neglect pivotal user-centered aspects, including trust-building, ethics, personalization, empathy, user comprehension, and emotional support. The purpose of this paper is to explore state-of-the-art LLM-based evaluation metrics that are specifically applicable to the assessment of interactive conversational models in healthcare. Subsequently, we present a comprehensive set of evaluation metrics designed to thoroughly assess the performance of healthcare chatbots from an end-user perspective. These metrics encompass an evaluation of language processing abilities, impact on real-world clinical tasks, and effectiveness in user-interactive conversations. Finally, we engage in a discussion concerning the challenges associated with defining and implementing these metrics, with particular emphasis on confounding factors such as the target audience, evaluation methods, and prompt techniques involved in the evaluation process.

BackgroundMachine learning (ML) has captured the attention of many clinicians who may not have formal training in this area but are otherwise increasingly exposed to ML literature that may be relevant to their clinical specialties. ML papers that follow an outcomes-based research format can be assessed using clinical research appraisal frameworks such as PICO (Population, Intervention, Comparison, Outcome). However, the PICO frameworks strain when applied to ML papers that create new ML models, which are akin to diagnostic tests. There is a need for a new framework to help assess such papers.ObjectiveWe propose a new framework to help clinicians systematically read and evaluate medical ML papers whose aim is to create a new ML model: ML-PICO (Machine Learning, Population, Identification, Crosscheck, Outcomes). We describe how the ML-PICO framework can be applied toward appraising literature describing ML models for health care.ConclusionThe relevance of ML to practitioners of clinical medicine is steadily increasing with a growing body of literature. Therefore, it is increasingly important for clinicians to be familiar with how to assess and best utilize these tools. In this paper we have described a practical framework on how to read ML papers that create a new ML model (or diagnostic test): ML-PICO. We hope that this can be used by clinicians to better evaluate the quality and utility of ML papers.

BackgroundPatient-centered outcomes research seeks to answer patient-centered questions. The process includes varied locations and individuals throughout the care continuum to address individual differences and constraints in implementation and dissemination.ProblemThis paper intends to answer this question: do academic nurses practice what they preach by assisting patient-centered outcomes research and researchers through their engagement with patients, caregivers, and other community stakeholder partners in nursing research?ApproachThis paper provides an overview of how academic nurses in a single institution (the University of Texas Medical Branch at Galveston School of Nursing) began to embrace patient-centered outcomes research.ConclusionWhether academic nurses are practicing what they preach in terms of patient-centered outcomes research remains uncertain. More examples from academia are required to make that determination. Academic nurses worldwide have embarked on a steep learning curve to embrace patient-centered outcomes research. This journey will require patience and a systematic strategy.

Background: As research involving human participants increasingly occurs with the aid of digital tools (e.g., mobile apps, wearable and remote pervasive sensors), the consent content and delivery process is changing. Informed consent documents to participate in research are lengthy and difficult for prospective participants to read and understand. As the consent communication will need to include concepts and procedures unique to digital health research, making that information accessible and meaningful to the prospective participant is critical for consent to be informed. This paper describes a methodology that researchers can apply when developing a consent communication for digital health research. Methods: A consent document approved by a US institutional review board was deconstructed into segments that aligned with federal requirements for informed consent. Three researchers independently revised each segment of text with a goal of achieving a readability score between a 6-8th grade level. The team then consulted with an external readability expert well-versed in revising informed consent documents into "plain language." The resulting text was evaluated using Microsoft Word and Online-Utility accessibility software. The final step involved adding visual images and graphics to complement the text. The Digital Health Checklist consent prototype builder was then used to identify areas where the consent content could be expanded to address four key domains of Access and Usability, Privacy, Risks and Benefits, and Data Management. Results: The approved consent was evaluated at a 12.6 grade reading level, whereas the revised language by our study team received 12.4, 12, and 12.58, respectively. The final consent document synthesized the most readable of the three revised versions and was further revised to include language recommended by the software tool for improving readability, which resulted in a final revised consent readability score of a 9.2 grade level. Moreover, word count was reduced from 6,424 in the original consent to 679 in the rewritten consent form. Conclusion: Utilizing an iterative process to design an accessible informed consent document is a first step in achieving meaningful consent to participate in digital health research. This paper describes how a consent form approved by an institutional review board can be made more accessible to a prospective research participant by improving the document readability score, reducing the word count and assessing alignment with the Digital Health Checklist.

BackgroundWe were tasked by the World Health Organization (WHO) to address the following question: What techniques should be used to diagnose Schistosoma infections in snails and in the water in potential transmission sites? Our goal was to review and evaluate the available literature and provide recommendations and insights for the development of WHO's Guidelines Development Group for schistosomiasis control and elimination.MethodologyWe searched several databases using strings of search terms, searched bibliographies of pertinent papers, and contacted investigators who have made contributions to this field. Our search covered from 1970 to Sept 2020. All papers were considered in a PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework, and retained papers were grouped by technique and subjected to our GRADE (Grading of Recommendations, Assessment, Development and Evaluations) evidence assessment profile determined in consultation with WHO. We also considered issues of sensitivity, specificity, coverage, cost, robustness, support needs, schistosome species discrimination, and relevant detection limits.Principal findingsOur PRISMA process began with the perusal of 949 articles, of which 158 were retained for data extraction and evaluation. We identified 25 different techniques and for each applied a GRADE assessment considering limitations, inconsistency, imprecision, indirectness, and publication bias. We also provide advantages and disadvantages for each category of techniques.ConclusionsOur GRADE analysis returned an assessment of moderate quality of evidence for environmental DNA (eDNA), qPCR and LAMP (Loop-mediated isothermal amplification). No single ideal diagnostic approach has yet been developed, but considerable recent progress has been made. We note a growing trend to use eDNA techniques to permit more efficient and replicable sampling. qPCR-based protocols for follow-up detection offer a versatile, mature, sensitive, and specific platform for diagnosis though centralized facilities will be required to favor standardization. Droplet digital PCR (ddPCR) can play a complementary role if inhibitors are a concern, or more sensitivity or quantification is needed. Snail collection, followed by shedding, is encouraged to provide specimens for sequence verifications of snails or schistosomes. LAMP or other isothermal detection techniques offer the prospect of less expensive and more distributed network of analysis but may face standardization and verification challenges related to actual sequences amplified. Ability to detect schistosome infections in snails or in the water is needed if control and elimination programs hope to succeed. Any diagnostic techniques used need to be regularly verified by the acquisition of DNA sequences to confirm that the detected targets are of the expected species. Further improvements may be necessary to identify the ideal schistosome or snail sequences to target for amplification. More field testing and standardization will be essential for long-term success.

The profound impact of food on health necessitates advanced nutrition-oriented food recommendation services. Conventional methods often lack the crucial elements of personalization, explainability, and interactivity. While Large Language Models (LLMs) bring interpretability and explainability, their standalone use falls short of achieving true personalization. In this paper, we introduce ChatDiet, a novel LLM-powered framework designed specifically for personalized nutrition-oriented food recommendation chatbots. ChatDiet integrates personal and population models, complemented by an orchestrator, to seamlessly retrieve and process pertinent information. The personal model leverages causal discovery and inference techniques to assess personalized nutritional effects for a specific user, whereas the population model provides generalized information on food nutritional content. The orchestrator retrieves, synergizes and delivers the output of both models to the LLM, providing tailored food recommendations designed to support targeted health outcomes. The result is a dynamic delivery of personalized and explainable food recommendations, tailored to individual user preferences. Our evaluation of ChatDiet includes a compelling case study, where we establish a causal personal model to estimate individual nutrition effects. Our assessments, including a food recommendation test showcasing a 92% effectiveness rate, coupled with illustrative dialogue examples, underscore ChatDiet's strengths in explainability, personalization, and interactivity.

ObjectiveBlockchain has emerged as a potential data-sharing structure in healthcare because of its decentralization, immutability, and traceability. However, its use in the biomedical domain is yet to be investigated comprehensively, especially from the aspects of implementation and evaluation, by existing blockchain literature reviews. To address this, our review assesses blockchain applications implemented in practice and evaluated with quantitative metrics.Materials and methodsThis systematic review adapts the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework to review biomedical blockchain papers published by August 2023 from 3 databases. Blockchain application, implementation, and evaluation metrics were collected and summarized.ResultsFollowing screening, 11 articles were included in this review. Articles spanned a range of biomedical applications including COVID-19 medical data sharing, decentralized internet of things (IoT) data storage, clinical trial management, biomedical certificate storage, electronic health record (EHR) data sharing, and distributed predictive model generation. Only one article demonstrated blockchain deployment at a medical facility.DiscussionEthereum was the most common blockchain platform. All but one implementation was developed with private network permissions. Also, 8 articles contained storage speed metrics and 6 contained query speed metrics. However, inconsistencies in presented metrics and the small number of articles included limit technological comparisons with each other.ConclusionWhile blockchain demonstrates feasibility for adoption in healthcare, it is not as popular as currently existing technologies for biomedical data management. Addressing implementation and evaluation factors will better showcase blockchain's practical benefits, enabling blockchain to have a significant impact on the health sector.

IntroductionBehavioral health emergencies (BHEs) are a common patient encounter for emergency medical services (EMS) clinicians and other first responders, in particular law enforcement (LE) officers. It is critical for EMS clinicians to have management strategies for BHEs, yet relatively little information exists on best practices. In 2016, the Los Angeles County EMS Agency's Commission initiated a comprehensive evaluation of the 9-1-1 response for BHEs and developed a plan for improving the quality of care and safety for patients and first responders.MethodsA Behavioral Health Initiative Committee was assembled with broad representation from EMS, LE, health agencies, and the public. Committee objectives included: 1) produce a process map of the BHE response from the time of a 9-1-1 call to patient arrival at transport destination, 2) identify and describe the different agencies that respond, 3) describe the critical decision points in the EMS and LE field responses, 4) acquire data that quantitatively and/or qualitatively describe the services available, and 5) recommend interventions for system performance improvement.ResultsThe committee generated comprehensive process maps for the prehospital response to BHEs, articulated principles for evaluation, and described key observations of the current system including: 9-1-1 dispatch criteria are variable and often defaults to a LE response, the LE response inadvertently criminalizes BHEs, EMS field treatment protocols for BHEs (and especially agitated patients) are limited, substance use disorder treatment lacks integration, destination options differ by transporting agency, and receiving facilities' capabilities to address BHEs are variable. Recommendations for performance improvement interventions and initial implementation steps included: standardize dispatch protocols, shift away from a LE primary response, augment EMS treatment protocols for BHEs and the management of agitation, develop alternate destination for EMS transport.ConclusionThis paper describes a comprehensive performance improvement initiative in LAC-EMSA's 9-1-1 response to BHEs. The initiative included a thorough current state analysis, followed by future state mapping and the implementation of interventions to reduce LE as the primary responder when an EMS response is often warranted, and to improve EMS protocols and access to resources for BHEs.

Health Psychology has received numerous papers over the past several months on topics related to the COVID-19 pandemic. Many of them concern depression, anxiety, stress, or other forms of distress in the general population or in health care workers. We have received far fewer papers on COVID-related health behaviors and health communications-factors that have played central roles in the spread of the pandemic and that are major topics in health psychology. Our experience is consistent with the published scientific literature on the pandemic. A Medline search that we conducted in late September yielded over 23,000 English-language articles pertaining to COVID-19. Over 1,400 of them concerned topics that are within the scope of Health Psychology. As shown in Table 1, COVID-related mental disorders comprised the largest category. Many other studies concerned other forms of stress or emotional distress. At least 248 articles addressed the profound ethnic and racial disparities in COVID-19 infection and death rates and in access to health care that are accentuating longstanding health inequities; 22 (9%) of these articles addressed behavioral or psychosocial aspects of COVID-19 health disparities. Thus, the literature on the behavioral and psychosocial aspects of the pandemic has been dominated, so far at least, by research on stress or distress. Fewer reports have been published so far on critical COVID-related health behaviors, health communication, or health disparities. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

In 2010, the Bill and Melinda Gates Foundation (BMGF) partnered with the Government of Bihar (GoB), India to launch the Ananya program to improve reproductive, maternal, newborn and child health and nutrition (RMNCHN) outcomes. The program sought to address supply- and demand-side barriers to the adoption, coverage, quality, equity and health impact of select RMNCHN interventions. Approaches included strengthening frontline worker service delivery; social and behavior change communications; layering of health, nutrition and sanitation into women's self-help groups (SHGs); and quality improvement in maternal and newborn care at primary health care facilities. Ananya program interventions were piloted in approximately 28 million population in eight innovation districts from 2011-2013, and then beginning in 2014, were scaled up by the GoB across the rest of the state's population of 104 million. A Bihar Technical Support Program provided techno-managerial support to governmental Health as well as Integrated Child Development Services, and the JEEViKA Technical Support Program supported health layering and scale-up of the GoB's SHG program. The level of support at the block level during statewide scale-up in 2014 onwards was approximately one-fourth that provided in the pilot phase of Ananya in 2011-2013. This paper - the first manuscript in an 11-manuscript and 2-viewpoint collection on Learning from Ananya: Lessons for primary health care performance improvement - seeks to provide a broad description of Ananya and subsequent statewide adaptation and scale-up, and capture the background and context, key objectives, interventions, delivery approaches and evaluation methods of this expansive program. Subsequent papers in this collection focus on specific intervention delivery platforms. For the analyses in this series, Stanford University held key informant interviews and worked with the technical support and evaluation grantees of the Ananya program, as well as leadership from the India Country Office of the BMGF, to analyse and synthesise data from multiple sources. Capturing lessons from the Ananya pilot program and statewide scale-up will assist program managers and policymakers to more effectively design and implement RMNCHN programs at scale through technical assistance to governments.

Burn care remains among the most complex of the time-sensitive treatment interventions in medicine today. An enormous quantity of specialized resources are required to support the critical and complex modalities needed to meet the conventional standard of care for each patient with a critical burn injury. Because of these dependencies, a sudden surge of patients with critical burn injuries requiring immediate and prolonged care following a burn mass casualty incident (BMCI) will place immense stress on healthcare system assets, including supplies, space, and an experienced workforce (staff). Therefore, careful planning to maximize the efficient mobilization and rational use of burn care resources is essential to limit morbidity and mortality following a BMCI. The U.S. burn care profession is represented by the American Burn Association (ABA). This paper has been written by clinical experts and led by the ABA to provide further clarity regarding the capacity of the American healthcare system to absorb a surge of burn-injured patients. Furthermore, this paper intends to offer responders and clinicians evidence-based tools to guide their response and care efforts to maximize burn care capabilities based on realistic assumptions when confronted with a BMCI. This effort also aims to align recommendations in part with those of the Committee on Crisis Standards of Care for the Institute of Medicine, National Academies of Sciences. Their publication guided the work in this report, identified here as "conventional, contingency, and crisis standards of care." This paper also includes an update to the burn Triage Tables- Seriously Resource-Strained Situations (v.2).

This supplement describes the content, processes, and outcomes of the Research Priorities in Caregiving Summit convened by the Family Caregiving Institute (FCI) at the Betty Irene Moore School of Nursing at UC Davis in March 2018. As described in the editorial introduction and the supplement's four papers, the summit sought to integrate and cross-pollenate the already compendious work on family caregiving to describe ways forward in the field. Thought-provoking commissioned synthesizing papers on issues of heterogeneity and trajectories of caregiving and its cultural embeddedness and on the potential of technology to shape and enhance caregiving interventions set the stage for a highly disciplined, multistaged process that resulted in the drafting of a set of research themes and priorities that were later finalized by faculty at the FCI.

ObjectiveTo evaluate informatics-enabled quality improvement (QI) strategies for promoting time spent on face-to-face communication between ophthalmologists and patients.MethodsThis prospective study involved deploying QI strategies during implementation of an enterprise-wide vendor electronic health record (EHR) in an outpatient academic ophthalmology department. Strategies included developing single sign-on capabilities, activating mobile- and tablet-based applications, EHR personalization training, creating novel workflows for team-based orders, and promoting problem-based charting to reduce documentation burden. Timing data were collected during 648 outpatient encounters. Outcomes included total time spent by the attending ophthalmologist on the patient, time spent on documentation, time spent on examination, and time spent talking with the patient. Metrics related to documentation efficiency, use of personalization features, use of team-based orders, and note length were also measured from the EHR efficiency portal and compared with averages for ophthalmologists nationwide using the same EHR.ResultsTime spent on exclusive face-to-face communication with patients initially decreased with EHR implementation (2.9 to 2.3 minutes, p = 0.005) but returned to the paper baseline by 6 months (2.8 minutes, p = 0.99). Observed participants outperformed national averages of ophthalmologists using the same vendor system on documentation time per appointment, number of customized note templates, number of customized order lists, utilization of team-based orders, note length, and time spent after-hours on EHR use.ConclusionInformatics-enabled QI interventions can promote patient-centeredness and face-to-face communication in high-volume outpatient ophthalmology encounters. By employing an array of interventions, time spent exclusively talking with the patient returned to levels equivalent to paper charts by 6 months after EHR implementation. This was achieved without requiring EHR redesign, use of scribes, or excessive after-hours work. Documentation efficiency can be achieved using interventions promoting personalization and team-based workflows. Given their efficacy in preserving face-to-face physician-patient interactions, these strategies may help alleviate risk of physician burnout.

Rural health care settings are challenged to provide timely and evidence-based care, particularly for culturally diverse patients with behavioral health disorders. Telepsychiatry and telebehavioral health improve access to care and leverage scarce resources. This scoping review from January 2000 - July 2019 was conducted to see if the literature had data for two related the research questions, "What are the components of culturally competent, telepsychiatric clinical care, and what approaches have clinicians and systems taken to implement and evaluate it?" The review focused on key words in four concept areas: (I) competencies; (II) telehealth in the form of telepsychiatry, telebehavioral or telemental health; (III) culture; and (IV) health. It was done in accordance with the six-stage scoping review process in PubMed/Medline and other databases. The screeners reviewed the full-text articles for final inclusion based on inclusion (mesh of the key words) and exclusion (e.g., need for only, skills abstractly discussed) criteria. From a total of 1,118 papers, the authors found 44 eligible for full text review and found 7 papers directly relevant to the concepts. Few studies specifically discuss skills and competencies of both telehealth and cultural factors. Many organizations are attending to cultural competencies and approaches to care, but there are no specific competencies that integrate telepsychiatry or telebehavioral health with culture. Existing telepsychiatric (i.e., video, social media, mobile health) and one set telebehavioral health competencies included cultural component, including use of interpreters and language matters. Administrative adjustments are suggested to promote culturally competent care by telehealth via clinical, educational, quality improvement, program/system evaluation, and other (e.g., finance and reimbursement) interventions. More structured research is needed on development, implementation and evaluation of combined competencies in rural settings.

BackgroundPatient engagement with diabetes self-care is critical to reducing morbidity and mortality. Social media is one form of digital health that is available for diabetes self-care, although its use for peer-to-peer communication has not been systematically described, and its potential to support patient self-care is unclear.ObjectiveThe primary aim of this systematic review was to describe the use of social media among patients (peer-to-peer) to manage diabetes and cardiovascular disease (CVD). The secondary aim was to assess patients' clinical outcomes, behavioral outcomes, quality of life, and self-efficacy resulting from peer-to-peer social media use.MethodsWe conducted a literature search in the following databases: PubMed, EMBASE, Web of Science, CINAHL, and PsycINFO (January 2008 through April 2019). The inclusion criteria were quantitative studies that included peer-to-peer use of social media for self-care of diabetes mellitus (with all subtypes) and CVD, including stroke.ResultsAfter an initial yield of 3066 citations, we selected 91 articles for a full-text review and identified 7 papers that met our inclusion criteria. Of these, 4 studies focused on type 1 diabetes, 1 study included both type 1 and 2 diabetes, and 2 studies included multiple chronic conditions (eg, CVD, diabetes, depression, etc). Our search did not yield any individual studies on CVD alone. Among the selected papers, 2 studies used commercial platforms (Facebook and I Seek You), 3 studies used discussion forums developed specifically for each study, and 2 surveyed patients through different platforms or blogs. There was significant heterogeneity in the study designs, methodologies, and outcomes applied, but all studies showed favorable results on either primary or secondary outcomes. The quality of studies was highly variable.ConclusionsThe future landscape of social media use for patient self-care is promising. However, current use is nascent. Our extensive search yielded only 7 studies, all of which included diabetes, indicating the most interest and demand for peer-to-peer interaction on diabetes self-care. Future research is needed to establish efficacy and safety in recommending social media use among peers for diabetes self-care and other conditions.

ObjectiveThe Mexican government has pursued multiple initiatives to improve healthcare coverage and financial protection. Yet, out-of-pocket health spending and use of private sector providers in Mexico remains high. In this paper, we sought to describe the characteristics of public and private healthcare users, describe recent visit quality across provider types, and to assess whether perceiving the public healthcare sector as poor quality is associated with private health sector use.Methods and findingsWe analyzed the cross-sectional People's Voice Survey conducted from December 2022 to January 2023. We used Chi-square tests to compare contextual, individual, and need-for-care factors and ratings of most recent visits between users of public (social security and other public providers) and private sector providers (stand-alone private providers and providers adjacent to pharmacies). We used a multivariable Poisson regression model to assess associations between low ratings of public healthcare sources and the use of private care. Among the 811 respondents with a healthcare visit in the past year, 31.2% used private sources. Private healthcare users were more educated and had higher incomes than public healthcare users. Quality of most recent visit was rated more highly in private providers (70.2% rating the visit as excellent or very good for stand-alone private providers and 54.3% for pharmacy-adjacent doctors) compared to social security (41.6%) and other public providers (46.6%). Those who perceived public health institutions as low quality had a higher probability of seeking private healthcare.ConclusionUsers rated public care visits poorly relative to private care; at the population level, perceptions of poor quality care may drive private care use and hence out-of-pocket costs. Improving public healthcare quality is necessary to ensure universal health coverage.

BackgroundHIV or sexually transmitted infections remain a significant public health concern in the United States, with adolescents affected disproportionately. Adolescents engage in HIV/STI risk behaviors, including drug use and condomless sex, which increase the risk for HIV/STIs. At-risk adolescents, many of whom are racial minorities, experience HIV/STI disparities. Although at-risk adolescents are disproportionately affected by HIV/STI risk behaviors and infections and although the Centers for Disease Control and Prevention recommends routine HIV/STI testing for adolescents, relatively few adolescents report having ever been tested for HIV/STI. With expected increases in health clinic visits as a result of the Affordable Care Act combined with technological advances, health clinics and mobile health (mHealth), including apps, provide innovative contexts and tools to engage at-risk adolescents in HIV/STI prevention programs. Yet, there is a dearth of efficacious mHealth interventions in health clinics to prevent and reduce both condomless sex and drug use and increase HIV/STI testing for at-risk adolescents.ObjectiveTo address this gap in knowledge, we developed a theory-driven, culturally congruent mHealth intervention (hereon referred to as S4E [Storytelling 4 Empowerment]) that has demonstrated feasibility and acceptability in a clinical setting. The next step is to examine the preliminary efficacy of S4E on adolescent HIV/STI testing and risk behaviors. This goal will be accomplished by 2 aims: the first aim is to develop a cross-platform and universal version of S4E. The cross-platform and universal version of S4E will be compatible with both iOS and Android operating systems and multiple mobile devices, aimed at providing adolescents with ongoing access to the intervention once they leave the clinic, and the second aim is to evaluate the preliminary efficacy of S4E, relative to usual care control condition, in preventing or reducing drug use and condomless sex and increasing HIV/STI testing in a clinical sample of at-risk adolescents aged 14-21 years living in Southeast Michigan.MethodsIn this study, 100 adolescents recruited from a youth-centered community health clinic will be randomized via blocked randomization with random sequences of block sizes to one of the 2 conditions: S4E mHealth intervention or usual care. Theory-driven and culturally congruent, S4E is an mHealth adaptation of face-to-face storytelling for empowerment, which is registered with the Substance Abuse and Mental Health Services Administration's National Registry of Evidence-Based Programs and Practices.ResultsThis paper describes the protocol of our study. The recruitment began on May 1, 2018. This study was registered on December 11, 2017, in ClinicalTrials.gov. All participants have been recruited. Data analysis will be complete by the end of March 2024, with study findings available by December 2024.ConclusionsThis study has the potential to improve public health by preventing HIV/STI and substance use disorders.Trial registrationClinicalTrials.gov NCT03368456; https://clinicaltrials.gov/study/NCT03368456.International registered report identifier (irrid)DERR1-10.2196/47216.

IntroductionThe rising burden of diabetes in low- and middle-income countries may cause financial strain on individuals and health systems. This paper presents a systematic review of direct medical costs for diabetes (types 1 and 2) in low- and middle-income countries.MethodsFollowing Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, databases (PubMed, International Bibliography of Social Science, EconLit) were searched for publications reporting direct medical costs of type 1 and 2 diabetes. Data were extracted from all peer-reviewed papers meeting inclusion criteria, and were standardised into per-patient-visit, per-patient-year and/or per-complication-case costs (2016 US$).ResultsThe search yielded 584 abstracts, and 52 publications were included in the analysis. Most articles were from Asia and Latin America, and most focused on type 2 diabetes. Per-visit outpatient costs ranged from under $5 to over $40 (median: $7); annual inpatient costs ranged from approximately $10 to over $1000 (median: $290); annual laboratory costs ranged from under $5 to over $100 (median: $25); and annual medication costs ranged from $15 to over $500 (median: $177), with particularly wide variation found for insulin. Care for complications was generally high-cost, but varied widely across countries and complication types.ConclusionThis review identified substantial variation in diabetes treatment costs; some heterogeneity could be mitigated through improved methods for collecting, analysing and reporting data. Diabetes is a costly disease to manage in low- and middle-income countriesand should be a priority for the global health community seeking to achieve Universal Health Coverage.

The first National Research Summit on Care, Services, and Supports for Persons with Dementia and Their Caregivers was held on October 16-17, 2017, at the National Institutes of Health. In this paper, participants from the Summit Session on Research on Care Needs and Supportive Approaches for Persons with Dementia summarize the state of the science, identify gaps in knowledge, and offer recommendations to improve science and practice in long-term care. Recommendations cover 4 areas focused on persons living with dementia: (1) symptoms (behavioral and psychological symptoms of dementia, function, cognition, and sleep); (2) dementia care settings (physical and social environments, home, and residential care); (3) living with dementia (living well with dementia, living alone with dementia, and living with dementia and intellectual and developmental disabilities); and (4) technology as a cross-cutting theme. The participants identify 10 of the most pressing research issues based on the findings from their collective papers. Final Summit recommendations included those presented by session participants and will be used to advise federal agencies and other organizations that fund research.

Multilevel service delivery frameworks are approaches to structuring and organizing a spectrum of evidence-based services and supports, focused on assessment, prevention, and intervention designed for the local context. Exemplar frameworks in child mental health include positive behavioral interventions and supports in education, collaborative care in primary care, and systems of care in community mental health settings. Yet, their high-quality implementation has lagged. This work proposes a conceptual foundation for multilevel service delivery frameworks spanning diverse mental health service settings that can inform development of strategic implementation supports. We draw upon the existing literature for three exemplar multilevel service delivery frameworks in different child mental health service settings to (1) identify core components common to each framework, and (2) to highlight prominent implementation determinants that interface with each core component. Six interrelated components of multilevel service delivery frameworks were identified, including, (1) a systems-level approach, (2) data-driven problem solving and decision-making, (3) multiple levels of service intensity using evidence-based practices, (4) cross-linking service sectors, (5) multiple providers working together, including in teams, and (6) built-in implementation strategies that facilitate delivery of the overall model. Implementation determinants that interface with core components were identified at each contextual level. The conceptual foundation provided in this paper has the potential to facilitate cross-sector knowledge sharing, promote generalization across service settings, and provide direction for researchers, system leaders, and implementation intermediaries/practitioners working to strategically support the high-quality implementation of these frameworks.

IntroductionNearly 30 000 Mexican women develop breast cancer annually, frequently presenting unmet supportive care needs. In high-income countries, incorporating electronic patient-reported outcomes (ePROs) into cancer care has demonstrated potential for increasing patient-centred care and reducing unmet needs. No such ePRO interventions have been implemented in Mexico. This paper presents the study protocol for designing and evaluating an ePRO digital health application combined with proactive follow-up by nurses.Methods and analysisWe designed a two-component intervention for women receiving breast cancer treatment: a responsive web application for monitoring ePROs and clinical algorithms guiding proactive follow-up by nurses. We will conduct a pilot test of the intervention with 50 patients with breast cancer for 6 weeks to assess feasibility and adjust the application. We will conduct a parallel arm randomised controlled trial assigning 205 patients each to intervention and control in one of Mexico's largest public oncology hospitals. The intervention will be provided for 6 months, with additional 3 months of post-intervention observation. The control group will receive usual healthcare and a list of breast cancer information sources. Women diagnosed with stages I, II or III breast cancer who initiate chemotherapy and/or radiotherapy will be invited to participate. The primary study outcome will be supportive care needs; secondary outcomes include global quality of life and breast symptoms. Information on the outcomes will be obtained through web-based self-administered questionnaires collected at baseline, 1, 3, 6 and 9 months.Ethics and disseminationThe National Research and Ethics Committees of the Mexican Institute of Social Security approved the study (R-2021-785-059). Participants will sign an informed consent form prior to their inclusion. Findings will be disseminated through a policy brief to the local authorities, a webinar for patients, publications in peer-reviewed journals and presentations at national and international conferences.Trial registration numberNCT05925257.

Sleep quality is crucial to both mental and physical well-being. The COVID-19 pandemic, which has notably affected the population's health worldwide, has been shown to deteriorate people's sleep quality. Numerous studies have been conducted to evaluate the impact of the COVID-19 pandemic on sleep efficiency, investigating their relationships using correlation-based methods. These methods merely rely on learning spurious correlation rather than the causal relations among variables. Furthermore, they fail to pinpoint potential sources of bias and mediators and envision counterfactual scenarios, leading to a poor estimation. In this paper, we develop a Causal Machine Learning method, which encompasses causal discovery and causal inference components, to extract the causal relations between the COVID-19 pandemic (treatment variable) and sleep quality (outcome) and estimate the causal treatment effect, respectively. We conducted a wearable-based health monitoring study to collect data, including sleep quality, physical activity, and Heart Rate Variability (HRV) from college students before and after the COVID-19 lockdown in March 2020. Our causal discovery component generates a causal graph and pinpoints mediators in the causal model. We incorporate the strongly contributing mediators (i.e., HRV and physical activity) into our causal inference component to estimate the robust, accurate, and explainable causal effect of the pandemic on sleep quality. Finally, we validate our estimation via three refutation analysis techniques. Our experimental results indicate that the pandemic exacerbates college students' sleep scores by 8%. Our validation results show significant p-values confirming our estimation.

Short Summary: The Letter to the Editors regarding our article was reviewed. The take-home message is that substantively, the authors of the letter are referencing a paper that asks a different research question in a different set of studies. When we ask different questions, we are not surprised when we reach different answers.

Health interventions using real-time sensing technology are characterized by intensive longitudinal data, which has the potential to enable nuanced evaluations of individuals' responses to treatment. Existing analytic tools were not developed to capitalize on this opportunity as they typically focus on first-order findings such as changes in the level and/or slope of outcome variables over different intervention phases. This paper introduces an exploratory, Markov-based empirical transition method that offers a more comprehensive assessment of behavioral responses when intensive longitudinal data are available. The procedure projects a univariate time-series into discrete states and empirically determines the probability of transitioning from one state to another. State transition probabilities are summarized separately in phase-specific transition matrices. Comparing transition matrices illuminates intricate, quantifiable differences in behavior between intervention phases. Statistical significance is estimated via bootstrapping techniques. This paper introduces the methodology via three case studies from a secondhand smoke reduction trial utilizing real-time air particle sensors. Analysis enabled the identification of complex phenomena such as avoidance and escape behavior in response to punitive contingencies for tobacco use. Additionally, the largest changes in behavior dynamics were associated with the introduction of behavioral feedback. The Markov approach's ability to elucidate subtle behavioral details has not typically been feasible with standard methodologies, mainly due to historical limitations associated with infrequent repeated measures. These results suggest that the evaluation of intervention effects in data-intensive single-case designs can be enhanced, providing rich information that can ultimately be used to develop interventions uniquely tailored to specific individuals.

A key component of the current framework for economic evaluation is the measurement and valuation of health outcomes using generic preference-based health-related quality-of-life (HRQoL) instruments. In 2015, a research synthesis reported the absence of conceptual and empirical research regarding the appropriateness of current preference-based instruments for people with aphasia-a disorder affecting the use and understanding of language-and suggested the development and validation of an accessible, pictorial variant could be an appropriate direction for further research. This paper describes the respective rationale and development process for each of three preliminary studies that have been undertaken to develop pictorial variants of two widely used preference-based HRQoL instruments (EQ-5D-3L and EQ-5D-5L). The paper also proposes next steps for this program of research, drawing on the lessons learned from the preliminary work and the demand for a pictorial preference-based instrument in the research community. Guidance for the use of the preliminary, pictorial instruments is also provided.

Objective To summarize significant contributions to sensor, signal, and imaging informatics literature published in 2017.Methods PubMed® and Web of Science® were searched to identify the scientific publications published in 2017 that addressed sensors, signals, and imaging in medical informatics. Fifteen papers were selected by consensus as candidate best papers. Each candidate article was reviewed by section editors and at least two other external reviewers. The final selection of the four best papers was conducted by the editorial board of the International Medical Informatics Association (IMIA) Yearbook.Results The selected papers of 2017 demonstrate the important scientific advances in management and analysis of sensor, signal, and imaging information.ConclusionThe growth of signal and imaging data and the increasing power of machine learning techniques have engendered new opportunities for research in medical informatics. This synopsis highlights cutting-edge contributions to the science of Sensor, Signal, and Imaging Informatics.

Social media data can provide valuable information regarding people's behaviors and health outcomes. Previous studies have shown that social media data can be extracted to monitor and predict infectious disease outbreaks. These same approaches can be applied to other fields including physical activity research and forensic science. Social media data have the potential to provide real-time monitoring and prediction of physical activity level in a given region. This tool can be valuable to public health organizations as it can overcome the time lag in the reporting of physical activity epidemiology data faced by traditional research methods (e.g. surveys, observational studies). As a result, this tool could help public health organizations better mobilize and target physical activity interventions. The first part of this paper aims to describe current approaches (e.g. topic modeling, sentiment analysis and social network analysis) that could be used to analyze social media data to provide real-time monitoring of physical activity level. The second aim of this paper was to discuss ways to apply social media analysis to other fields such as forensic sciences and provide recommendations to further social media research.

Introduction: The effect of stigma on health and health inequity is increasingly recognized. While many medical conditions trigger stigmatization, the negative effects of HIV stigma are particularly well documented. HIV stigma undermines access, uptake, and adherence to both HIV prevention and treatment. People living with HIV face stigma in all aspects of their daily lives; however, stigma in the health system is particularly detrimental. A key component for health facility stigma-reduction interventions is participatory training of staff, often through several days of in-person training. Though this approach shows promise, it is time intensive and poses challenges for busy health facilities. In response, the DriSti study has developed a brief blended-learning approach to stigma reduction in Karnataka State, India. This paper describes the process and final content of the intervention development. The intervention is currently being tested. Final evaluation results will be published upon study completion. Methods: Grounded in behavior change strategies based on social cognitive theory principles that stress the importance of combining interpersonal interactions with specific strategies that promote behavior change, we used a three-phase approach to intervention development: (1) content planning-review of existing participatory stigma-reduction training activities; (2) story boarding-script development and tablet content production; and (3) pilot testing of tablet and in-person session materials. Results: The final intervention curriculum consists of three sessions. Two initial self-administered tablet sessions focus on stigma awareness, attitudes, fears of HIV transmission, and use of standard precautions. The third small group session covers the same material but includes skill building through role-play and testimony by a person living with HIV. A study team member administers the tablet sessions, explains the process, and is present throughout to answer questions. Conclusion: This paper describes the theoretical underpinning and process of developing the blended-learning curriculum content, and practical lessons learned.The approach covers three key drivers of HIV stigma-stigma awareness, fear of HIV transmission, and attitudes. Developing video content for the self-directed learning is complex, requires a diverse set of people and skills, and presents unexpected opportunities for stigma reduction. Co-facilitation of the in-person session by someone living with HIV is a critical component.

Patient reported measures (PRMs), including patient-reported outcomes, play a critical role in dialysis care. The usage of PRMs is extensive in dialysis clinics. While there are excellent PRMs to choose from, and their implementation as part of quality improvement and performance monitoring is extensive, there are still methodological challenges to be addressed. In this paper, we identify key methodological concerns around use of PRMs in dialysis centers in the United States and make recommendations for improving the use of PRMs in dialysis related to Selection of PRMs, Mode of Administration, and Support for PRM Use. These recommendations include: (1) Continue the use of Kidney Disease Quality of Life 36-item survey (KDQOL™-36) for dialysis centers' internal quality improvement activities and the In-Center Hemodialysis Consumer Assessment of Health Care Providers and Systems (ICH-CAHPS survey®) for public dialysis center performance monitoring, but promote efforts to modify these instruments by incorporating PROMIS general health items (KDQOL-36) and reducing the length of the ICH-CAHPS. (2) Adopt a PRM of whether dialysis patients have been informed about all dialysis and transplant options. (3) Evaluate equivalence between electronic and paper versions of PRMs prior to widespread use of electronic administration. (4) Explore reimbursement of costs of PRM administration by the Centers for Medicare and Medicaid Services and kidney organizations. (5) Continue development of provider trainings in PRM administration and interpretation. These recommendations will help dialysis care decision-makers, clinicians, and applied researchers take the next steps toward enhancing PRM use in dialysis.

BackgroundHealth information systems are central to strong health systems. They assist with patient and program management, quality improvement, disease surveillance, and strategic use of information. Many donors have worked to improve health information systems, particularly by supporting the introduction of electronic health information systems (EHIS), which are considered more responsive and more efficient than older, paper-based systems. As many donor-driven programs are increasing their focus on country ownership, sustainability of these investments is a key concern. This analysis explores the potential sustainability of EHIS investments in Malawi, Zambia and Zimbabwe, originally supported by the United States President's Emergency Plan for AIDS Relief (PEPFAR).MethodsUsing a framework based on sustainability theories from the health systems literature, this analysis employs a qualitative case study methodology to highlight factors that may increase the likelihood that donor-supported initiatives will continue after the original support is modified or ends.ResultsFindings highlight commonalities around possible determinants of sustainability. The study found that there is great optimism about the potential for EHIS, but the perceived risks may result in hesitancy to transition completely and parallel use of paper-based systems. Full stakeholder engagement is likely to be crucial for sustainability, as well as integration with other activities within the health system and those funded by development partners. The literature suggests that a sustainable system has clearly-defined goals around which stakeholders can rally, but this has not been achieved in the systems studied. The study also found that technical resource constraints - affecting system usage, maintenance, upgrades and repairs - may limit EHIS sustainability even if these other pillars were addressed.ConclusionsThe sustainability of EHIS faces many challenges, which could be addressed through systems' technical design, stakeholder coordination, and the building of organizational capacity to maintain and enhance such systems. All of this requires time and attention, but is likely to enhance long-term outcomes.

Working in an interdisciplinary manner at the crossroads of alcohol and HIV research is a challenge. This paper presents six novel approaches that could be applied to activities at the intersection of alcohol and HIV. These approaches are (i) address the fact that the availability of new technology is unevenly distributed around the world, (ii) use technology to move beyond both paper and digital surveys, (iii) introduce a focus on advocacy and partnerships with large technology companies, (iv) harness technological innovation to utilise digital counselling, (v) explore the use of virtual reality in both research and delivering interventions, and (vi) consider alternative funding models to those currently in existence to improve efficiencies and innovations. Aiming to understand the interplay of alcohol and HIV will require creativity. The six approaches outlines in this paper provide possible directions from which new approaches may emerge.

In this paper, performance of hurdle models in rare events data is improved by modifying their binary component. The rare-event weighted logistic regression model is adopted in place of logistic regression to deal with class imbalance due to rare events. Poisson Hurdle Rare Event Weighted Logistic Regression (REWLR) and Negative Binomial Hurdle (NBH) REWLR are developed as two-part models which use the REWLR model to estimate the probability of a positive count and a Poisson or NB zero-truncated count model to estimate non-zero counts. This research aimed to develop and assess the performance of the Poisson and Negative Binomial (NB) Hurdle Rare Event Weighted Logistic Regression (REWLR) models, applied to simulated data with various degrees of zero inflation and to Nairobi county's maternal mortality data. The study data on maternal mortality were pulled from JPHES. The data contain the number of maternal deaths, which is the outcome variable, and other obstetric and demographic factors recorded in MNCH facilities in Nairobi between October 2021 and January 2022. The models were also fit and evaluated based on simulated data with varying degrees of zero inflation. The obtained results are numerically validated and then discussed from both the mathematical and the maternal mortality perspective. Numerical simulations are also presented to give a more complete representation of the model dynamics. Results obtained suggest that NB Hurdle REWLR is the best performing model for zero inflated count data due to rare events.

BackgroundDementia can impede the relationship and connection between the person with dementia (PWD) and their caregiver. Yet, caregiving in dementia also offers opportunities for connection, which has implications for caregiver and PWD well-being. In this qualitative study, we describe and characterize ways caregivers felt connected to the person with dementia they care for.MethodsWe conducted a telephone-based survey with caregivers of people with dementia. For this paper, we analyzed responses to an open-ended question focused on when caregivers feel most connected to the person they are caring for. Responses were analyzed and coded and themes were identified through an iterative process involving a multidisciplinary team of researchers and clinicians.Results437 caregivers participated in this study. We identified two domains of connection: activity-based and emotion-based connections. Within activity-based connections, the following themes emerged: everyday activities; reminiscing; activities of caregiving; novel experiences; and time with family and friends. Within emotional connections, the following themes emerged: expressions of love, appreciation, and gratitude; physical affection; sharing an emotion or emotional experience; and times when the PWD seems like "themself" again.ConclusionsFindings provide insights into ways caregivers experience a sense of connection with the person they care for. There is a call to shift away from focusing on reducing stress and toward optimizing positive experiences as a way to better support caregivers' health and well-being. Interventions that leverage these insights to foster caregiver - PWD connection could lead to better health and well-being for both members of the dyad. The amplification of a positive experience may be particularly important for caregivers who are struggling with limited support or respite. Clinicians may be interested in using a question about connection as a way to more fully understand a caregiver's current experience.

IntroductionThe rapid scale-up of HIV care and treatment in resource-limited countries requires concurrent, rapid development of health information systems to support quality service delivery. Mozambique, a country with an 11.5% prevalence of HIV, has developed nation-wide patient monitoring systems (PMS) with standardized reporting tools, utilized by all HIV treatment providers in paper or electronic form. Evaluation of the initial implementation of PMS can inform and strengthen future development as the country moves towards a harmonized, sustainable health information system.ObjectiveThis assessment was conducted in order to 1) characterize data collection and reporting processes and PMS resources available and 2) provide evidence-based recommendations for harmonization and sustainability of PMS.MethodsThis baseline assessment of PMS was conducted with eight non-governmental organizations that supported the Ministry of Health to provide 90% of HIV care and treatment in Mozambique. The study team conducted structured and semi-structured surveys at 18 health facilities located in all 11 provinces. Seventy-nine staff were interviewed. Deductive a priori analytic categories guided analysis.ResultsHealth facilities have implemented paper and electronic monitoring systems with varying success. Where in use, robust electronic PMS facilitate facility-level reporting of required indicators; improve ability to identify patients lost to follow-up; and support facility and patient management. Challenges to implementation of monitoring systems include a lack of national guidelines and norms for patient level HIS, variable system implementation and functionality, and limited human and infrastructure resources to maximize system functionality and information use.ConclusionsThis initial assessment supports the need for national guidelines to harmonize, expand, and strengthen HIV-related health information systems. Recommendations may benefit other countries with similar epidemiologic and resource-constrained environments seeking to improve PMS implementation.

Background Currently, malaria elimination efforts are ongoing in several locations across Southeast Asia,  including in Kayin State (also known as Karen State), Myanmar . This paper describes the community engagement efforts for a pilot malaria elimination project, the challenges encountered and lessons learnt.Methods Between May 2013 and June 2015, a study on targeted malaria elimination (TME) that included mass drug administration was conducted in four villages (TPN, TOT, KNH, and HKT) of Kayin State. Community engagement efforts included workshops, meetings and house-to-house visits with community members.  Exhibitions related to malaria and fun activities were organized for children. In addition, we provided primary care, small individual incentives and village-level incentives. This paper is based on our analysis of data extracted from meeting minutes, field notes, feedback sessions among staff and with community members as well as our own reflections.Results Average participation across three rounds of MDA were 84.4%, 57.4%, 88.6% and 59.3% for TPN, TOT, KNH and HKT, respectively. Community engagement was fraught with practical challenges such as seasonal tasks of the villagers. There were challenges in explaining difficult concepts like drug resistance and submicroscopic infection. Another was understanding and navigating the politics of these villages, which are located in politically contested areas.  Managing expectations of villagers was difficult as they assumed that the community team must know everything related to health.Conclusions In the TME project, many different community engagement strategies were employed. We encountered many challenges which included logistical, scientific and political difficulties.  An approach that is tailored to the local population is key.

BACKGROUND:Calls for evidence-informed public health policy, with implicit promises of greater program effectiveness, have intensified recently. The methods to produce such policies are not self-evident, requiring a conciliation of values and norms between policy-makers and evidence producers. In particular, the translation of uncertainty from empirical research findings, particularly issues of statistical variability and generalizability, is a persistent challenge because of the incremental nature of research and the iterative cycle of advancing knowledge and implementation. This paper aims to assess how the concept of uncertainty is considered and acknowledged in World Health Organization (WHO) policy recommendations and guidelines. METHODS:We selected four WHO policy statements published between 2008-2013 regarding maternal and child nutrient supplementation, infant feeding, heat action plans, and malaria control to represent topics with a spectrum of available evidence bases. Each of these four statements was analyzed using a novel framework to assess the treatment of statistical variability and generalizability. RESULTS:WHO currently provides substantial guidance on addressing statistical variability through GRADE (Grading of Recommendations Assessment, Development, and Evaluation) ratings for precision and consistency in their guideline documents. Accordingly, our analysis showed that policy-informing questions were addressed by systematic reviews and representations of statistical variability (eg, with numeric confidence intervals). In contrast, the presentation of contextual or "background" evidence regarding etiology or disease burden showed little consideration for this variability. Moreover, generalizability or "indirectness" was uniformly neglected, with little explicit consideration of study settings or subgroups. CONCLUSION:In this paper, we found that non-uniform treatment of statistical variability and generalizability factors that may contribute to uncertainty regarding recommendations were neglected, including the state of evidence informing background questions (prevalence, mechanisms, or burden or distributions of health problems) and little assessment of generalizability, alternate interventions, and additional outcomes not captured by systematic review. These other factors often form a basis for providing policy recommendations, particularly in the absence of a strong evidence base for intervention effects. Consequently, they should also be subject to stringent and systematic evaluation criteria. We suggest that more effort is needed to systematically acknowledge (1) when evidence is missing, conflicting, or equivocal, (2) what normative considerations were also employed, and (3) how additional evidence may be accrued.

The predominant clonal evolution (PCE) model seeks to formulate a common population genetics framework for all micropathogens (namely, parasitic protozoa, fungi and yeasts, bacteria, and viruses). It relies on a definition of clonality that is only based on population structure features (namely, strongly restrained genetic recombination). Its clear-cut properties make it of strong interest for applied and basic research, since it permits the definition of stable, clearly delimited units of analysis below the species level: clonal genotypes and discrete genetic subdivisions ("near-clades"). These units of analysis can be used for clinical and epidemiological studies, vaccine and drug design, species description, and evolutionary studies on natural and experimental populations. In this review, the evolutionary and population genetics background of the model will be only briefly mentioned, while considerable emphasis will be given to its practical significance for the study and control of neglected tropical diseases. The goal of the paper is to make this practical usefulness accessible to a broad audience of readers, including scientists who are not evolution specialists, such as epidemiologists, field scientists, and clinicians. For extensive developments about the evolutionary background of the model, see our previous papers [1-9]. Citations of these former articles lead to the many references quoted in them, which cannot be listed again here.

BackgroundDespite the rapid growth in the sophistication of research on bipolar disorder (BD), the field faces challenges in improving quality of life (QoL) and symptom outcomes, adapting treatments for marginalized communities, and disseminating research insights into real-world practice. Community-based participatory research (CBPR)-research that is conducted as a partnership between researchers and community members-has helped address similar gaps in other health conditions. This paper aims to improve awareness of the potential benefits of CBPR in BD research.MethodsThis paper is a product of the International Society for Bipolar Disorders (ISBD) Taskforce on Community Engagement which includes academic researchers, healthcare providers, people with lived experience of BD, and stakeholders from BD community agencies. Illustrative examples of CBPR in action are provided from two established centres that specialize in community engagement in BD research: the Collaborative RESearch Team to study psychosocial issues in BD (CREST.BD) in Canada, and the Spectrum Centre for Mental Health Research in the United Kingdom.Results and discussionWe describe the philosophy of CBPR and then introduce four core research areas the BD community has prioritized for research: new treatment approaches, more comprehensive outcome assessments, tackling stigma, and enhanced understanding of positive outcomes. We then describe ways in which CBPR is ideal for advancing each of these research areas and provide specific examples of ways that CBPR has already been successfully applied in these areas. We end by noting potential challenges and mitigation strategies in the application of CBPR in BD research.ConclusionsWe believe that CBPR approaches have significant potential value for the BD research community. The observations and concerns of people with BD, their family members, and supports clearly represent a rich source of information. CBPR approaches provide a collaborative, equitable, empowering orientation to research that builds on the diversity of strengths amongst community stakeholders. Despite the potential merits of this approach, CBPR is as yet not widely used in the BD research field, representing a missed opportunity.

In 2006, the Institute of Medicine published a report titled "Emergency Care for Children: Growing Pains," in which it described pediatric emergency care as uneven at best. Since then, telehealth has emerged as one of the great equalizers in care of children, particularly for those in rural and underresourced communities. Clinicians in these settings may lack pediatric-specific specialization or experience in caring for critically ill or injured children. Telehealth consultation can provide timely and safe management for many medical problems in children and can prevent many unnecessary and often long transport to a pediatric center while avoiding delays in care, especially for time-sensitive and acute interventions. Telehealth is an important component of pediatric readiness of hospitals and is a valuable tool in facilitating health care access in low resourced and critical access areas. This paper provides an overview of meaningful applications of telehealth programs in pediatric emergency medicine, discusses the impact of the COVID-19 pandemic on these services, and highlights challenges in setting up, adopting, and maintaining telehealth services.