Political, social, economic, and health system determinants play an important role in creating an enabling environment for maternal and newborn health. This study assesses changes in health systems and policy indicators for maternal and newborn health across 78 low- and middle-income countries (LMICs) during 2008–2018, and examines contextual factors associated with policy adoption and systems changes.We compiled historical data from WHO, ILO, and UNICEF surveys and databases to track changes in ten maternal and newborn health systems and policy indicators prioritized for tracking by global partnerships. Logistic regression was used to examine the odds of systems and policy change based on indicators of economic growth, gender equality, and country governance with available data from 2008 to 2018.From 2008 to 2018, many LMICs  substantially strengthened systems and policies for maternal and newborn health. The most frequently adopted policies were national guidelines for kangaroo mother care, national guidelines for use of antenatal corticosteroids, national policies for maternal death notification and review, and the introduction of priority medicines in Essential Medicines Lists. The odds of policy adoption and systems investments were significantly greater in countries that experienced economic growth, had strong female labor participation, and had strong country governance .The widespread adoption of priority policies over the past decade is a notable step in creating an environment supportive for maternal and newborn health, but continued leadership and resources are needed to ensure robust implementation that translates into improved health outcomes. •From 2008 to 2018, many LMICs adopted policies supportive of maternal and newborn health.•Many adopted guidelines for kangaroo mother care and use of antenatal corticosteroids.•Many also adopted national policies for maternal death notification and review.•The odds of policy adoption were greater in certain contexts.•Economic growth, gender equality, and governance may facilitate policy adoption. The global maternal mortality ratio declined by 38 percent between 2000 and 2017 , and neoA multitude of diverse factors contribute to the success or failure of countries to achieve maternal and newborn survival goals . These iThe increasing recognition of the importance of the health systems and policy environment has fueled demand for data to monitor policy adoption and health systems investments, but until recently, limited data were available for multi-country comparisons or for tracking trends over time . This st2We used country indicators from three rounds of WHO SRMNCAH policy surveys and other WHO, ILO, and UNICEF databases for corresponding years. All WHO member states were eligible to participate in SRMNCAH policy surveys . The ana2.1To assess changes in MNH systems and policies, we compiled data on ten tracer indicators . These rWe also identified contextual factors related to economic growth, gender equality, and country governance, hypothesized to influence adoption of MNH policies and health system investments. These included gross domestic production (GDP) growth per capita, percentage of seats held by women in national parliaments, labor force participation by females, and composite governance scores for voice and accountability, political stability and absence of violence, government effectiveness, regulatory quality, rule of law, and control of corruption.2.2Data sources included WHO SRMNCAH policy surveys, WHO Global Health Workforce Statistics Database, WHO Global Health Expenditure Database (GHED), WHO Global Maternal Death Surveillance and Response (MDSR) implementation survey, WHO & UNICEF Marketing of Breast-milk Substitutes: National Implementation of the International Code Status Reports, ILO World Social Protection Reports, ILO Working Conditions Laws Database, and the ILO NORMLEX database . World  AdditionAfter compiling data on selected indicators for all available years between 2008 and 2018, we reviewed changes in each indicator across years and across data sources on a country-by-country basis. We flagged any inconsistencies that might indicate a reporting error . If an inconsistency was found, we reviewed the relevant source documents  issued by the country to validate the data; if warranted, we recoded variables to align with the content and publication date of the original source document(s).2.3We described each indicator for available years between 2008 and 2018. Data for indicators collected from surveys were generally available at three time points: 2008, 2014/15, and 2018; countries that did not respond to surveys in a given year were reported as missing and excluded from the calculation of percentages for the corresponding year. Other indicators were generally available annually. To smooth fluctuations and provide estimates for missing years, we fit mixed-effects models to, first, model the average change in health workforce density over time for a given country, and then separately, model the average change in GGHE per capita over time for a given country. This approach to modeling multilevel, longitudinal data allows us to represent country differences with a random intercept and, also, to model country-specific trends over time with a random slope . .Next, we classified how each indicator changed over the time period on a country-by-country basis, comparing data for the earliest available year  to 2018 data. For binary indicators measuring policy adoption, we categorized changes as: (a) already in existence since 2008 (or the earliest available year); (b) adopted by 2018; or (c) not adopted by 2018. For categorical indicators measuring alignment of legislation with international conventions, we categorized as: (a) legislation already ratified or substantially aligned in 2008; (b) strengthened during 2008–2018; or (c) not strengthened during 2008–2018. Changes in health worker density were categorized in the following manner: (a) already attained SDG index threshold of at least 44.5 doctors, nurses, and midwives per 10,000 population in 2008 and remained at or above threshold; (b) above average increase in health worker density during 2008–2018 relative to other countries in the sample; (c) minimal to average increase during 2008–2018; or (d) decrease during 2008–2018. Similarly, we categorized changes in GGHE per capita as: (a) country invested at least $150 per capita in 2008 and value remained at threshold or increased; (b) above average growth in GGHE per capita during 2008–2018 relative to other countries in the sample; (c) minimal to average growth during 2008–2018; or (d) decrease during 2008–2018.We then summarized the data to classify countries into five categories based on the overall level of change in the MNH systems and policy environment: “remained strong” ; “strengthened” ; “limited change” ; “reversals” ; or “mixed changes”  . The reference group included countries that had “limited change”, “mixed changes”, or “reversals” (n = 30), with a total sample size of 74 countries. Countries with a strong MNH systems and policy environment in 2008 that “remained strong” were excluded from the model, because they were considered as having reached a ceiling wherein further policy adoption and systems investments would no longer be feasible, irrespective of continued improvements in economic growth, gender equality, or governance.We hypothesized that having high levels of economic growth, gender equality, and country governance in 2008 may increase the likelihood of MNH systems strengthening and policy adoption. We also hypothesized that changes in indicators of economic growth, gender equality, and country governance during 2008–2018  may affect the likelihood of MNH systems and policy change. We fit multiple univariable regression models to estimate the odds of substantial MNH systems and policy change based on the initial 2008 value of each indicator and, separately, the change in each indicator's value between 2008 and 2018. Changes in GDP per capita were measured as the difference in natural log (ln) GDP per capita between 2008 and 2018, rescaled to measure incremental changes of 0.1 ln-units, which is equivalent to a change of 10.5% in GDP per capita. Changes in female parliamentary representation were measured as the absolute difference in percentages between 2008 and 2018. Governance scores and female labor participation were relatively stable during 2008–2018, so we did not assess whether changes in these indicators were associated with the outcome .We used Stata version 15.1 for all statistical analyses . The 2012.4Sensitivity analysis applied an alternative approach to examine whether MNH systems and policies were associated with indicators of economic growth, gender equality, and country governance. For regression modeling, we specified the outcome as the number of MNH systems and policies in existence—or which had reached a minimum threshold—at the end of the reference period in 2018, with a maximum score of 10 indicating the country had all ten MNH systems and policy tracer indicators. A linear regression model examined the association between having a greater number of MNH systems and policies in existence and indicators of economic growth, gender equality, and country governance.2.5The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report.3Of the 136 WHO member countries classified as LMICs, 112 (82%) responded to the 2018 SRMNCAH survey and 78 (58%) also had historical information available on MNH systems and policy indicators. Our analysis focuses on these 78 countries . CompareBetween 2008 and 2018, many countries adopted key MNH policies and invested in systems relevant for MNH . The mosFewer changes were seen in the legislative context relative to other policy areas. Only one-fifth  of countries strengthened legal provisions for paid maternity leave . Some prOverall, while more than half of countries  substantially strengthened the MNH systems and policy environment between 2008 and 2018, some countries  saw limited change, a few  saw reversals, and others  saw both improvements and reversals . The odd4Every Woman Every Child (EWEC) movement to mobilize action for women's, children's, and adolescents' health. This was followed by the establishment of the UN Commission on Life-Saving Commodities for Women and Children and the UN Commission on Information and Accountability, the launch of ENAP and EPMM, and the publication of various technical guidance documents and recommendations  on maternity protection in 2000, and maternity benefit coverage is also now an indicator for the SDGs (1.3.1). While most countries have enacted at least some legal provisions for maternity leave, the duration and level of benefits are often limited and eligibility restricted to those employed in the formal economy. Coverage is worse in low-income countries, where only 10·5% of women giving birth received maternity care benefits in 2020 . Forty yDelivering maternal and newborn health services depends on having adequate financial and human resources for health. A systemic bottleneck analysis conducted with over 600 experts as part of the Lancet's Every Newborn Series identified health workforce and financing as common constraints to MNH care . Our resCountries that substantially strengthened the MNH systems and policy environment between 2008 and 2018 were more likely to be those that also experienced economic growth and had strong country governance. An analysis of data from 143 countries over 14 years found that GDP growth was associated with increased government health expenditures . FurtherHowever, the mere adoption of MNH-friendly policies and strengthened systems are not sufficient to improve MNH outcomes. While enacting favorable policies and improving systems can create an enabling environment that facilitates the scale-up of effective interventions, it does not guarantee robust implementation nor widespread coverage of these interventions. For example, Torres et al. described achievements integrating kangaroo mother care into national policy in six priority countries, but noted the proportion of small newborns initiated in kangaroo mother care remains low . Studieshttps://platform.who.int/data/maternal-newborn-child-adolescent-ageing/national-policies). The portal allows users to review country-specific health systems and policy indicators, visualize data using charts and maps, and search a repository of national laws, strategies, and policy documents. Such resources can provide policymakers, implementers, and researchers with information on the legal and policy environment in different countries, and they can facilitate future analyses and dialogue on policy options to improve MNH.Our study provides a useful point of entry for understanding the MNH policy and systems environment globally, but country-specific analyses are likewise critical to understanding the political, social, economic, and health system determinants that influence MNH within the local context. Our study analyzes data from several sources, including a global policy survey of WHO Member States on laws, policies, and strategies relevant for MNH. This data is also available to the public on the Maternal, Newborn, Child, and Adolescent Health and Ageing Data Portal . This study is limited by its focus on a few, tangible variables that can be measured and quantified.Another limitation of the study is the variability of data quality. Many indicators are self-reported by country teams; often, representatives from the Ministry of Health and/or focal points at various partners worked together to complete policy surveys and respond to requests for information . Validat5Overall, our study finds the policy and systems landscape for MNH is changing in many LMICs. We document widespread adoption of several priority MNH policies and guidelines, including guidelines for kangaroo mother care and antenatal corticosteroids, policies related to maternal death surveillance and response systems, and the integration of priority maternal and newborn medicines on EMLs. The adoption of these policies and guidelines are a notable step in creating an environment supportive of MNH, but continued leadership and resources are needed to strengthen implementation of these policies and guidelines. Dialogue to understand and address the barriers and facilitators encountered by actors at different levels of the health system can strengthen implementation and help ensure that evidence-based policies and guidelines translate into tangible improvements for maternal and newborn health and wellbeing.10.13039/100000865Bill & Melinda Gates Foundation [INV-009058].This work was supported, in whole or in part, by the The authors alone are responsible for the views expressed in this article and they do not necessarily represent the views, decisions or policies of the institutions with which they are affiliated.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


Rapid technological advancement in high-throughput genomics, microarray, and deep sequencing technologies has accelerated the possibility of more complex precision medicine research using large amounts of heterogeneous health-related data from patients, including genomic variants. Genomic variants can be identified and annotated based on the reference human genome either within the sequence as a whole or in a putative functional genomic element. The American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) mutually created standards and guidelines for the appraisal of proof to expand consistency and straightforwardness in clinical variation interpretations. Various efforts toward precision medicine have been facilitated by many national and international public databases that classify and annotate genomic variation. In the present study, several resources are highlighted with recognition and data spreading of clinically important genetic variations. Over the last 50 years, genetics has evolved in line with genomic technologies such as DNA sequencing , and curWith the development of next-generation sequencing (NGS), researchers can easily identify the genetic sequences in the human genome . This fuGenome annotation is the process of identifying functional elements in the sequence of a genome. Based on the characteristics of genomics and genetics, the variants can be categorized or prioritized for further research. The genome that has been sequenced is not completed without an annotation process, which will help determine its clinical consequences. This information is fundamental for the practice of personalized medicine. Therefore, it is important to create a convergence between human genetics, molecular biology, biochemistry, and bioinformatics in such a way that the combination of their knowledge-pools enables arriving at an understanding over how variations of DNA exist in traits and diseases .Human DNA consists of single nucleotide polymorphisms (SNP), mutations, and copy number variants (CNVs). These variants constitute a cause for the differentiation of individuals based on their unique traits, including disease susceptibility and pharmacogenomics. The understanding of our genome is not only useful for the geneticist but also relevant to those working on tools and health development .The 2022 study of Samuels et al.  is a recIn this review, we discuss the features, strengths, and weaknesses of various resources as well as the establishment of a genomics variants database, i.e., the Malaysian Node of the Human Variome Project Database (MyHVPDb) and countries in Asia. We hope that this review will be useful for low and middle-income countries (LMIC) in establishing their own database for their population. This review also highlights how genomic variants are classified.https://grenada.lumc.nl/LSDB_list/lsdbs).There are a few resources presently available that provide the basic information that is required in genetic annotation . As of thttp://www.ncbi.nlm.nih.gov/clinvar/), to provide information about the relationships between human variants and phenotypes, and this information predominantly assumes the form of clinical interpretation and supporting evidence [The National Center for Biotechnology Information (NCBI) has developed a database, ClinVar (evidence . In addihttp://www.lrg-sequence.org) was established to curate the variants with clinical implications and contains stable genomic DNA sequences, transcript, and protein reference sequences for reporting clinically relevant sequence variants [Locus Reference Genomic (LRG)  that can be used to filter and prioritize pathogenic candidate mutations among the Thai population [Several LMICs have established their own ethnic-specific genome databases in preparation for future implementation of personalized medicine. As an example, Thailand has developed the Thai Reference Exome (T-REx) variant database (pulation . T-REx ipulation .www.iranome.com). This database contains 1,575,702 variants, of which 308,311 were novel variants (19.6%). The clinical information in this database can be a useful tool for categorizing the pathogenicity of uncommon mutations [In the same context, Iran has genotyped 800 individuals from 8 major ethnic groups, which has contributed to establishing the Iranome database  version 3. LOVD is widely used for the standard variant databases system for the collection, display, and curation of DNA variants including phenotypes and diseases . The curThe Singapore Genome Variation Project (SGVP) provided a publicly available resource of 1.6 million SNPs in the past 12 years that were genotyped in 268 individuals from the Chinese, Malay, and Indian population groups in Southeast Asia . This prIn Indonesia, a developing country, approximately 2500–5000 babies are born each year with a clinical pattern of beta-thalassemia major and beta-thalassemia intermedia , 67. TheIn general, DNA diagnosis is not routinely performed in the health service, and diagnosis of suspected thalassemia individuals usually comprises complete blood count and hemoglobin electrophoresis . SeveralThe American College of Medical Genetics and Genomics (ACMG) Standards and Guidelines were predominantly developed as an educational guideline for clinical laboratory geneticists, to assist them in providing a quality clinical laboratory service .In 2015, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) released joint recommendations for interpreting variants in genes associated with Mendelian disorders. These recommendations are part of an effort to establish a common framework for variant classification based on a standardized and transparent assessment of different lines of evidence. ACMG Guidelines provide several levels of evidence to ascertain the clinical significance of each genomic variant. However, there is still a challenging task to determine the pathogenicity of variants, especially in cancer. Several factors and information need to be taken into account as each genomic alteration can have an extent of much clinical efficacy, such as the diagnosis, prognosis, therapy selection, and monitoring, though only a few cancers have strong evidence of pathogenicity . Until nFigure 1). The variants are classified into these 5 categories according to different types of evidence including population data, computational data, functional data, and segregation data. This framework defined 28 evidence criteria organized by type and strength, which are used to classify the variants into the 5 categories. The framework proposed by the guidelines, encompassing various genes, diseases, and inheritance patterns, is intended for general use; however, to effectively execute the process of variant interpretation, expert judgment in evaluating and weighing evidence is needed.” By using the guidelines, a mutation is characterized by a change in the DNA base sequence, whereas a polymorphism is characterized by a frequency of greater than 1%. Both mutation and polymorphism were later changed to “variant” to avoid confusion arising from inaccurate assumptions of pathogenic or benign effects [The ACMG–AMP Guidelines propose the use of specific terminology, namely “pathogenic,” “likely pathogenic,” “uncertain significance,” “likely benign,” and “benign,” to characterize variants in Mendelian disorders .The Clinical Genome Resource (ClinGen) convenes all Variant Curation Expert Panels (VCEPs) to perform gene- and disease-specific modifications to the ACMG–AMP framework for variants related to a particular disease and inheritance pattern . Additiohttps://clinicalgenome.org/affiliation/vcep/#ep_table_heading). Figure 2 indicates the parameters used by the ClinGen Hemoglobinopathy VCEP for annotation variants in disorders of hemoglobinopathies.The current effort of ClinGen is the development of the ClinGen Variant Curation Interface (VCI). The ClinGen VCI is a global open-source variant classification platform that helps with the use of evidence criteria and the classification of variants based on the ACMG–AMP variant classification guidelines. There are 43 VCEPs and the majority are in the process of the establishment  was initiated in 2015 to accelerate and enhance the understanding of precision medicine and to take into consideration factors such as genetics, physiology, and environmental parameters for ascertaining the best approach to disease treatment for any individual patient . PreviouPrecision medicine will aid physicians to choose the best treatment and prevention approach for each patient according to their personal health information and their genetic makeup . CertainVarious efforts toward precision medicine have been facilitated by many national and international public databases that classify and annotate genomic variation , includiAdditionally, a decision from expert panels for variant annotation might be one of the challenges in precision medicine. Experts disclose that the disadvantages of personalized medicine are classifiable into 3 recognized issues, which are validity uncertainty, equity issues, and implementation . TherefoIn clinical settings, AI facilitates clinicians to work more efficiently to make diagnoses more accurate. Additionally, AI helps companies in drug development to implement time and cost-effective measures as well as prevent errors in the system.Globally, there are many initiatives to predict, with a high level of accuracy, which treatment and prevention strategies would be an appropriate choice for any particular disease that may present in a population. A primary challenge for clinical laboratories is to determine, with adequate evidence, the genes that can be associated with clinical findings and patients’ phenotypes. Therefore, ClinGen developed a method to help the community in this effort to assess the strength of evidence for each gene in specific diseases. ClinGen  is a multi-institutional initiative to standardize gene and variant curation as well as to improve the utility of genomics in medicine. ClinGen developed a method to evaluate the strength of evidence for providing supporting claims for every gene that causes particular diseases. Additionally, this effort was purposely initiated to establish an authoritative central resource for the characterization of clinically relevant genes and variants for precision medicine and future research .ClinGen gene and variant curation is currently organized into 8 Clinical Domain Working Groups (CDWG) to emphasize on curation and standardization efforts in clarification. These CDWG include Cardiovascular, Hearing Loss, Hemostasis or Thrombosis, Hereditary Cancer, Inborn Errors of Metabolism, Neurodevelopmental, Neuromuscular, and RASopathies (mutations in genes of the Ras-MAPK pathway). Each CDWG manages numerous Gene or Variant Curation Expert Panels (GCEPs or VCEPs) performing curation activities on gene sets and diseases within the domain group .As the ACMG–AMP Variant Interpretation Guidelines clarify and specify, ClinGen VCI curates the variants and expert review, and the VCEPs can provide interpreted variant sets to ClinVar and the ClinGen evidence repository . This step encourages the sharing of data from diagnostic laboratories, creation of consensus interpretations, and development of a collection of gene-specified ACMG–AMP evidence codes, thereby paving the way for eventually ensuring more accurate interpretations for clinical use .However, the critically important factor would also depend on ancestry and population reference data that are supported by previous data, developed through a detailed clinical investigation of affected patients and at-risk family members . As the In the era of precision medicine, variant discovery and annotation are required for diagnosis, prevention, and therapy improvement, based on an individually tailored approach; however, progress is still slow and the application of precision medicine in patients’ treatment still needs enhancement. Despite the abundance of raw data, much genetic variation in the human genome still remains uncharacterized. For precision medicine initiatives to progress, it is crucial that the discovery and annotation pipeline for novel variants also be incorporated during the analysis and interrogation of genomic data. Providing a uniform set of annotation resources for certain genetic diseases will ease comparisons and the interpretation of results. It is hoped that the discovery of novel genomic variants and their annotations would accelerate the development of precision medicine, thus benefitting mankind.


Lack of engagement is a common challenge for digital health interventions. To achieve their potential, it is necessary to understand how best to support users’ engagement with interventions and target health behaviors. The aim of this systematic review was to identify the behavioral theories and behavior change techniques being incorporated into mobile health apps and how they are associated with the different components of engagement.The review was structured using the PRISMA and PICOS frameworks and searched six databases in July 2022: PubMed, Embase, CINAHL, APA PsycArticles, ScienceDirect, and Web of Science. Risk of bias was evaluated using the Cochrane Collaboration Risk of Bias 2 and the Mixed Methods Appraisal Tools.A descriptive analysis provided an overview of study and app characteristics and evidence for potential associations between Behavior Change Techniques (BCTs) and engagement was examined.The final analysis included 28 studies. Six BCTs were repeatedly associated with user engagement: goal setting, self-monitoring of behavior, feedback on behavior, prompts/cues, rewards, and social support. There was insufficient data reported to examine associations with specific components of engagement, but the analysis indicated that the different components were being captured by various measures.This review provides further evidence supporting the use of common BCTs in mobile health apps. To enable developers to leverage BCTs and other app features to optimize engagement in specific contexts and individual characteristics, we need a better understanding of how BCTs are associated with different components of engagement.https://www.crd.york.ac.uk/prospero/, identifier CRD42022312596. Mobile health applications have the potential to empower people to improve their health behaviors and self-manage health conditions . They arThe conceptualization of engagement has recently become a focus in digital health research, resulting in several theories and frameworks . It is gAlthough evidence is still developing, previous research has emphasized the importance of incorporating behavioral theory into digital health intervention design . BehavioDespite the growing presence of Behavior Change Techniques (BCTs)  in mobilThe Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) framework  was usedThe eligibility criteria and search strategy were based on the PICOS framework . The proPubMed, Embase, Cumulative Index to Nursing and Allied Health Literature (CINAHL), APA PsycArticles, ScienceDirect, and Web of Science were searched using the search structure : engagemReferences were imported into EndNote X9 for duplicate removal and initial screening using the EndNote search function . One revData was extracted by one reviewer into a predetermined form see .General study information● Year of publication● Country of study● Sample demographics ● Initial sample size● Analyzed sample size● Study durationMobile health app behavioral intervention● App name● Operating platform ● Target health behavior● Aim of the intervention● Behavioral theory used● Number of included Behavior Change Techniques  (if any)● List of included Behavior Change Techniques  (if any)● Other app engagement featuresEvaluation● Component(s) of engagement examined● Engagement outcome measures● Effect of intervention on engagement outcomes● Effect of intervention on behavioral outcomes (if reported)● Effect of intervention on health outcomes (if reported)A descriptive analysis summarized study and intervention characteristics. A quantitative meta-analysis of effect was not possible due to outcome variety, so extracted evidence was analyzed by one author to map potential associations between BCTs and engagement. Evidence for potential associations was divided into three categories: evidenced, hypothesized, or inferred. Associations were inferred if studies did not report app features as BCTs or did not directly examine associations between features and engagement. Features were coded using the Behaviour Change Technique (BCT) Taxonomy v1  as generThe quality appraisal was conducted using the Cochrane Collaboration Risk of Bias 2 (RoB 2) tool for randomized controlled trials (RCTs)  and the Clinicaltrials.gov registration from which a full text article was identified.In total, 21,185 articles were retrieved and 28 were determined to be eligible for inclusion. The reasons for exclusion in the full-text review stage are included in the PRISMA flow diagram . One of The characteristics of the 28 included studies are summarized in Twenty-five individual apps were examined in 25 studies , with thThe most common method of measuring engagement (11/28 studies) was through app usage data . Other methods included surveys, qualitative methods, app-collected data (active or passive), and data from synced devices  and cognitive (11/21) components of engagement. Although affective engagement was seldom a stated outcome, a couple common affective-related themes were identified in several qualitative studies, notably “motivation” and “fun” . ParticiVarious constructs related to affective engagement were also captured in various questionnaires: irritation , sense of empathizing from app  inspiration/encouragement , fun and entertainment (uMARS engagement section), and visual appeal  , “hedoniData related to cognitive engagement also came primarily from qualitative feedback , althougThe risk of bias of the six randomized trials was evaluated using the Cochrane Collaboration RoB 2 tool . The domThe Mixed-Methods Appraisal Tool (MMAT)  was usedIn total, 28 studies that developed or examined mobile apps for health behavior change were examined to investigate how behaviour change techniques (BCTs) could influence different components of engagement. Although a variety of methods were used and various components of engagement could be identified in the data captured, most studies did not purposefully examine these different components. Different measures tended to capture different components: affective and cognitive engagement were primarily captured with qualitative methods, micro behavioral engagement with app use data, and macro behavioral engagement with self-report, questionnaires, and app tracking. This emphasizes the importance of mixed methods to fully assess user engagement. By combining study-reported evidence with our coding of BCTs and engagement, we identified patterns of evidence that suggest the potential of 6 BCTs to support engagement with digital health interventions: social support, goal setting, feedback, prompts/cues, self-monitoring, and rewards. A lack of explicit reporting of BCTs and preplanned analyses of engagement components limited our ability to identify potential associations between BCTs and specific components of engagement.The BCTs identified as having evidence of associations with engagement are in line with previous findings. The mixed influence of social support on engagement has also been observed by previous research  and coulThe broad scope is both a strength and a limitation; the inclusive search strategy reduced the likelihood of missing relevant studies, but necessitated automated screening. To mitigate the risk of screening out relevant studies, we used a set of six articles identified in preliminary searches and determined to be eligible to check the screening. After each pass in EndNote, if any of the six studies were missing, the search terms were revised and the pass re-run to ensure we were not incorrectly eliminating relevant papers. Although the search terms were developed with a second author, the review was not independently executed by two reviewers, which would have reduced the risk of bias in the analysis and increased the credibility of the conclusions. It was not possible to have a second reviewer due to time and resource constraints.The diversity of outcomes examined by the studies prohibited a quantitative meta-analysis to examine effect. Additionally, the studies examined a wide variety of health apps, aimed at various populations and behaviors. In including this variety of studies, the review is limited in its ability to explore potential context-specific associations. Contextual factors such as behavior, age, culture, app type, and outcomes could influence engagement in ways that it was not possible to capture with the current sample. The study was also limited to apps that had been evaluated in scientific investigations; this method risks excluding popular publicly-available apps that have not been previously evaluated. A review of the BCTs included in such apps and how they are associated with engagement could provide additional insights to inform app design.This study instead contributes to the literature by analyzing the body of evidence to hypothesize associations between BCTs and engagement for future testing. The analysis was limited by the available reported data and descriptions of the studies’ apps and measures. The lack of explicit analyses of engagement components in the included studies meant the review relied on author coding and inference to identify potential associations. As such, this review represents a starting point for further investigation of engagement and an identification of current limitations in digital health methodology and reporting.One of the challenges of our analysis was that there were no clear and comprehensive definitions of affective, cognitive, and behavioral engagement in the literature. Constructs commonly associated with affective engagement included motivation, positive and negative feelings, and sometimes aesthetic pleasure, while cognitive engagement was described using terms such as interest, attention, thought, and challenge . Recent There was not sufficient evidence available in the included studies to posit associations between BCTs and specific components of engagement. However, the exploratory analysis enables some hypotheses to be suggested for further investigation. Several of the BCTs with potential associations with engagement - goal setting, self-monitoring, feedback, social support, rewards, and prompts and cues - were identified as being “motivating” and “fun” for users. This evidence could indicate associations between these BCTs and affective and cognitive engagement, although further context about how and why they were motivating it would be needed to determine whether the associations were primarily affective, cognitive, or both. A theoretical examination of those components compared to the Behaviour Change Technique (BCT) taxonomy can provide some additional insight.The Human Behavior Change Project’s Theory and Techniques Tool maps the BCT taxonomy with mechanisms of action (MoA) . A couplRecent studies have identified a lack of justification and guidance for the operationalization of BCTs . The eviFor app developers, the key takeaways from the evidence gathered in this review is that the inclusion of BCTs such as goal setting, feedback, prompts/cues, self-monitoring, and reward could help support users’ engagement with mobile health apps. Social support also has the potential to support engagement, but can have unintended negative effects, depending on how it is incorporated. Based on the studies reviewed, our recommendation for developers considering incorporating social support is to carefully consider how it will be operationalized and to make that feature optional for users. Practical social support, such as linking patients with healthcare providers, is likely to support engagement and team-based competition seems to be less likely than individual competition to generate negative emotions in users. In view of app design, there appears to be a balance needed to obtain the optimal level of cognitive load. Data from participants indicated a preference for a reduced cognitive load - limited complexity, less data input, limited number of features, not time-consuming  - while The purpose of this systematic review was to incorporate theoretical conceptualizations of engagement and synthesize evidence of how mobile health apps and their BCTs are associated with different components of user engagement. Six BCTs were identified as having the most evidence of a potential association with engagement with digital behavior change interventions: goal setting, self-monitoring of behavior, feedback on behavior, prompts/cues, rewards, and social support. An exploratory analysis of the engagement components identified key areas for future research, including further theoretical clarity of engagement components, how less researched BCTs might be theoretically linked to engagement components, and how BCTs can be operationalized in app design to best support affective, cognitive, and behavioral engagement. Recommendations for app development deriving from the findings are the inclusion and further investigation of the 6 BCTs identified to support engagement and the importance of identifying the right level of cognitive involvement for the target population to keep the app interesting without being a burden. This review contributes to the body of evidence for the influence of specific BCTs on engagement by identifying a gap between theoretical conceptualizations of engagement and its evaluation in mobile health apps and hypothesizing potential associations for future empirical investigation. Greater clarity in the definitions of different components of engagement, and further development and incorporation of means of measuring specific types of engagement, could enable future research to examine how different components of engagement are related to specific BCTs and behavioral and health outcomes. This knowledge could inform the design and tailoring of mobile health apps to improve engagement with the intervention and target behaviors.The original contributions presented in this study are included in the article/MM-I conceived the topic, drafted the protocol, conducted the searches, screening, data extraction and analysis, and wrote the first draft of the manuscript. SH and JA contributed to the revisions. EM performed the final review and supervised the execution of the review. All authors contributed to the article and approved the submitted version.


Imaging tests are one of the most frequently used diagnostic modalities in healthcare, but the benefits of their direct impacts on clinical decision-making have been countered by concerns that they can be overused. Assessing the relative value of imaging tests has largely focused on measures of test accuracy, which overlooks more comprehensive benefits and risks of imaging tests, particularly their impact on patient-centred outcomes (PCOs). We present the findings of the Patient Reported Outcomes of Diagnostics (PROD) research study in response to a methodological gap in the area of diagnostic test comparative effectiveness research.Over a 3-year period, the PROD Study engaged with multiple stakeholders to identify existing conceptual models related to PCOs for imaging testing, conducted primary research and evidence synthesis, and developed consensus recommendations to describe and categorise PCOs related to imaging testing.The PROD framework categorises PCOs from imaging studies within four main domains: information or knowledge yielded, physical impact, emotional outcomes and test burden. PCOs interact with each other and influence effects across domains, and can be modified by factors related to the patient, clinical situation, healthcare team and the testing environment.Using PCOs to inform healthcare decision-making will require ways of collating and presenting information on PCOs in ways that can inform patient–provider decision-making, and developing methods to determine the relative importance of outcomes (including test accuracy) to one another. Multiple frameworks have been developed to evaluate diagnostic tests, which typically include generating evidence across phases of technical efficacy, test accuracy, diagnostic efficacy, therapeutic efficacy, patient outcome and societal aspects.The concept that tests can impact patient well-being, in addition to ‘clinical’ outcomes,The Patient Reported Outcomes of Diagnostics (PROD) StudyOur approach was based on the multistep processes used to develop consensus methods and research reporting guidelines.We used an iterative process to identify published literature that had attempted to address the methodological gap, including an extensive search of existing research on diagnostic test evaluation and imaging tests specifically. This was used to provide additional justification for the proposed research and identify any additional evaluation frameworks for diagnostic tests, conceptual models outlining the range of PCOs that may occur with testing, and literature specific to PCOs from imaging tests. We used a non-systematic scan of the literature search, including existing systematic reviews,http://becertain.org/partnerships/patient-advisory-network); (2) primary care clinicians and radiology staff from the Washington, Wyoming, Alaska, Montana and Idaho Practice and Research Network; (3) the American College of Radiology (ACR); (4) consumer advocates; (5) imaging industry and (6) diagnostic methods experts. Recruitment was based on a combination of outreach through national, regional and local organisations. The stakeholders guided research direction, informed data collection instruments, interpreted findings and contributed to research outputs.We adopted the Six-Stage Model for Patient-Centered Outcomes Research and Comparative Effectiveness Research to guide stakeholder engagement.In order to identify the frequency and type of PCOs reported in studies of imaging testing that are used to inform clinical recommendations, we conducted a secondary analysis of studies included in the ACR’s Diagnostic Imaging Appropriateness Criteria which are used by referring physicians and radiologists to guide imaging test decisions and are incorporated into clinical decision support mechanisms. We used a broad definition of PCOs used by Patient Centered Outcomes Research Institute (PCORI) and modified by other researchers in this field.We conducted semistructured interviews with 45 patients who had undergone imaging studies across a variety of conditions and imaging modalities, 16 primary care providers, and 16 radiologists and radiology technologists to seek their experiences and perceptions of PCOs.A scoping review of qualitative studies reporting PCOs from imaging studies was used to broaden the evidence base of PCOs beyond those identified from our primary research. We searched for studies reporting PCOs across multiple imaging modalities and clinical settings. The review aimed to identify relevant studies that had explored patients’ emotions, knowledge, and physical preferences in relation to imaging tests either before, during, or after imaging testing. The scoping review, described in full in 10.1136/bmjqs-2021-013311.supp1Supplementary dataet al.At the end of the 3-year period, 28 stakeholders  participThe work was funded by the PCORI, which approved the research plan submitted by the research team, but had no input to the research methods, findings, development of consensus recommendations, nor in preparation or approval for any manuscripts submitted for publication.All primary qualitative studies conducted by the authors, which are referenced in this manuscript, were approved by the University of Washington Division of Human Subject as documented in those publications.We identified several recommendations from groups such as guideline development organisations from the USA and Europe, and the Grading of Recommentations Assessment, Development and Evaluation (GRADE) Working Group that supported a need for methods to measure the effects of tests on PCOs.The secondary analysis of the ACR Appropriateness Criteria identified 89 eligible studies; these covered a wide range of clinical areas and imaging modalities.Analysis of interviews with 45 patients, 16 primary care providers, and 16 radiologists and radiology technologists identified four themes related to PCOs.We identified 25 qualitative studies that described PCOs, mainly focusing on mammography and MRI scanning, and most related to cancer screening, conducted in multiple countries . We idenThe stakeholder meeting facilitated discussion and feedback on proposed PCOs, domains and recommendations. The PROD team developed a matrix which proposed PCOs occurring across a range of domains, before, during and after an imaging test. This matrix was shared with stakeholders to develop consensus regarding the full scope of potential PCOs and categorisation into potential domains. The main outcomes, described below, categorised PCOs within four domains, outlined how PCOs can potentially interact with each other and identified factors that can modify how they are experienced.PCOs in this domain included test information that contributes to determining an underlying cause for patients’ symptoms or concerns, or information that led to reducing the likelihood of a condition . In addiPreparing for imaging tests was associated with specific unpleasant experiences, such as undergoing bowel preparation prior to colonography . HoweverTests used to evaluate new and/or concerning symptoms provided reassurance and relief when results ruled out certain conditions . Even inOutcomes related to the direct or indirect burdens of imaging tests  includedIn addition to the outcomes categorised within these four domains, PCOs interacted with, and influenced, outcomes in other domains. These interactions included, for example, knowledge or information provided by a test result (domain 1) influencing patients’ emotions (domain 3), or, a test that is more physically unpleasant (domain 2) that provides more valuable information (domain 1) than one that is less invasive. The pattern of interactions appeared to be complex and varied with factors such as test modality and clinical situation. Recognising these interactions exist suggests that weighing of risks and benefits across domains is likely to be challenging to incorporate into research or clinical care.Multiple factors potentially impacted or modified whether or not a PCO occurred, its severity, its relative importance and its impact on the patient .28 TheseThe Institute of Medicine highlighted that patient-centred practices are needed to address the psychological and social dimensions of patients’ healthcare concerns, in order to close quality gaps in healthcare.Our research advances an earlier concept that tests have more than ‘medical value’.et al, namely credibility, applicability, auditability and confirmability.A strength of our recommendations is that they were informed by a wide body of primary and secondary research, and relied also on extensive input from a range of stakeholders, and are applicable to imaging testing generally, rather than one type of test  or a single imaging modality. We used consensus methods, following key steps that have been recommended for this type of process.The current focus on accuracy in evaluating imaging tests  risks ignoring outcomes that may be meaningful from patients’ perspectives; it is the balance of outcomes that are important to patients, their caregivers and clinicians.In order to advance the use of PCOs in research and implementation of imaging testing, we propose several next steps . First, Box 1Validated measurement instruments for the full range of PCOs.Outcomes collected from patients themselves.Methods to rank the importance of individual PCOs, and to balance positive  and negative (harmful) outcomes, considering their severity, impact, timing of outcome.Expanded standards for reporting PCOs in evaluation of imaging tests.Information on PCOs that can be collected and meaningfully shared with patients and the healthcare team to inform decision-making.This box was created by the authors and no permission is required.Finally, measuring PCOs is of little value if it fails to inform healthcare decision-making and quality of care.


The autonomic nervous system (ANS) is responsible for the precise regulation of tissue functions and organs and, thus, is crucial for optimal stress reactivity, adaptive responses and health in basic and challenged states . The fine-tuning of central ANS activity relies on the internal central autonomic regulation system of the central autonomic network (CAN), while the peripheral activity relies mainly on the two main and interdependent peripheral ANS tracts, the sympathetic nervous system (SNS) and the parasympathetic nervous system (PNS). In disease, autonomic imbalance is associated with decreased dynamic adaptability and increased morbidity and mortality. Acute or prolonged autonomic dysregulation, as observed in stress-related disorders, affects CAN core centers, thereby altering downstream peripheral ANS function. One of the best established and most widely used non-invasive methods for the quantitative assessment of ANS activity is the computerized analysis of heart rate variability (HRV). HRV, which is determined by different methods from those used to determine the fluctuation of instantaneous heart rate (HR), has been used in many studies as a powerful index of autonomic (re)activity and an indicator of cardiac risk and ageing. Psychiatric patients regularly show altered autonomic function with increased HR, reduced HRV and blunted diurnal/circadian changes compared to the healthy state. The aim of this article is to provide basic knowledge on ANS function and (re)activity assessment and, thus, to support a much broader use of HRV as a valid, transdiagnostic and fully translational dynamic biomarker of stress system sensitivity and vulnerability to stress-related disorders in neuroscience research and clinical psychiatric practice. In particular, we review the functional levels of central and peripheral ANS control, the main neurobiophysiologic theoretical models , the precise autonomic influence on cardiac function and the definition and main aspects of HRV and its different measures . We also provide recommendations for the proper use of electrocardiogram recordings for HRV assessment in clinical and research settings and highlight pathophysiological, clinical and research implications for a better functional understanding of the neural and molecular mechanisms underlying healthy and malfunctioning brain–heart interactions in individual stress reactivity and psychiatric disorders. Assessing autonomic (re)activity is vital for the affective, cognitive and physical neuroscientific field, and should not only be used as a theoretical ground for further research, but also as a starting point for clinical applications. Although autonomic imbalance can be easily measured, these possibilities are, however, generally used sparsely by clinicians. The aim of this article is to provide basic knowledge on autonomic function and assessment and to support a much broader use of heart rate variability (HRV) as a valid, transdiagnostic and fully translational  dynamic biomarker of stress system sensitivity and vulnerability to stress-related disorders in research and clinical practice. Here, we review the functional levels of central and peripheral autonomic control, the main underlying neurobiophysiologic theoretical models, the pathways of autonomic influence on cardiac function and the definition and main aspects of HRV and its different assessment measures . We also provide recommendations for the proper use of electrocardiogram recordings for HRV assessment in clinical and research settings and highlight pathophysiological, clinical and research implications for a better functional understanding of the neural and molecular mechanisms underlying healthy and malfunctioning brain-heart interaction in individual stress reactivity and psychiatric disorders.Stress is defined as a state of threatened homeodynamic balance ,2 in an The ANS, although not under overt voluntary control (autonomous), plays a crucial role in the maintenance of homeodynamic balance by providing rapid and precise regulation of organ and tissue functions such as the respiratory, cardiovascular, digestive, endocrine systems and many other systems, and by adjusting to ongoing physical, emotional and cognitive challenges, resting state and sleep ,9. On thThe central autonomic network (CAN) mediates the task- and division-specific regulatory control of central pathways for peripheral autonomic regulation . The CANOne of the most appropriate systems for the functional assessment of ANS activity is the cardiovascular system, as responses of the effector tissues are prompt, easy to access and have a high clinical and prognostic value ,29. The The heart features a number of different effector tissues: the sinoatrial (SA) node, the atrioventricular (AV) node, the atrial and the ventricular myocardium . ModulatResting heart activity is under constant tonic inhibitory control by the PNS and its dominance over the SNS ,37. In a1A receptor activation [1A receptor overactivation in mice copies the cardiovascular effects of selective serotonin reuptake inhibitors (SSRIs) overdosing in humans as described in the FDA recommendation on the SSRI Citalopram (see http://www.fda.gov/drugs/drugsafety/ucm297391.htm (accessed on 10 April 2023)).Although the cardiovascular system is particularly appropriate for the functional assessment of ANS activity, standard cardiac measures  offer only limited information on ANS activity, as short- and long-term HR variations are not considered. One of the best established and most widely used non-invasive methods for the quantitative assessment of ANS activity is the computerized analysis of heart rate variability (HRV) ,42. HRV tivation , an incrAlthough HRV is a useful biomarker, there is no common agreement on which of the many available HRV measures to use in research and clinical practice. HRV measures can mainly be divided in two main categories: linear and nonlinear measures .Using linear algorithms, HRV can be analyzed in time or frequency domain. Standard time and frequency domain parameters were defined by the 1996 Task Force on HRV and are the most commonly used HRV measures.Time domain indexes are the first measures applied and are a basic way to calculate HRV as they are based on the normalized time between two detected heartbeat QRS events . Time domain HRV indexes are strictly correlated with each other and are normally calculated as standard deviation of the NN intervals (SDNN), the root mean square of subsequent interval differences (RMSSD), and the percentage of the number of pairs of adjacent NN intervals that differ in length by >50 ms (NN50%). Low SDNN, NN50 and RMSSD denote low vagal tone .Frequency domain indexes are more elaborated measures based on spectral analysis (fast Fourier transformation) and are mostly used to assess HRV. Frequency measures represent the power (energy) as a function of frequency with regard to specific frequency bands commonly based on fast Fourier transformation [ormation . HRV in ormation . Efferenormation ,47. The ormation . This alormation . Anothern+1 is represented on the Y-axis, RRn on the X-axis. Various parameters describe the Poincaré plot, with SD1 and SD2 being the most commonly used. SD1 is the dispersion (standard deviation) of the distribution of points perpendicular to the line of identity, and is a measure of short-term HRV. SD2 is the dispersion of the cloud of points along the line of identity, and is a measure of long-term HRV.A third, less frequently used form of analysis is the Poincaré plot analysis. The Poincaré plot of RR intervals, commonly described as a nonlinear measure, is not described by indexes that reflect nonlinear features of HRV  but showα = 1.0, indicating the persistent long-range correlation of successive heartbeat intervals, is observed in all physiological HR dynamics across mammalian species (incl. mice and man). Pathological states are characterized by a breakdown of long-range correlations, with an α strongly deviating from 1.0. An α = 1.5 reflects ‘Brownian noise’ and only indicates a short-term correlation between one heartbeat interval and the next one, and is observed as a blocked tonic parasympathetic outflow to the heart  [α = 0.5 indicates ‘white noise’ and a randomness by showing a lack of any correlation between heartbeat intervals. A breakpoint in the straight-line relationship separates slopes of coefficients into different distinct ranges, αfast and αslow  [Two major functional properties of HR dynamics, non-stationarity (drift-like behavior of HR) and interdependence , formally require the assessment of HR dynamics by non-standard methods to determine the organization of any apparently ‘noisy’ HR signal with its internal correlation and level of complexity . Nonlinentation) . An α = scaling) .Given that nonlinear analyses are scale-invariant, they can provide functional information about the dynamics of heartbeat interval fluctuations which can be used translationally between animal models and humans  . In addiFinally, multifractal ,52,56 anOne of the most important issues is how to record ECG in a standardized manner , for exaAnother important precondition for HRV analyses is proper quality control for detection of the R-peaks of the ECG signal. Compared to processed raw data, commercial systems often provide only suboptimal ECG detection algorithms. These algorithms may only negligibly affect HR analyses and are not sensitive enough for time domain measures such as RMSSD or nonlinear measures. Consequently, a combination of time-consuming manual and computerized editing by experienced scientists is obligatory before actual data analysis is performed. Last but not least, studies investigating HRV measures should always control for received medication which may affect HRV and should account for a range of important factors and/or exclusion criteria , that may otherwise confound the results and conclusions. A diagram depicting the individual steps from ECG recording to data analysis is shown in In human research, HRV reflects individual capacity for physiological and emotional regulation. In relation to this, recent studies have suggested HRV as a biomarker to monitor emotional regulation in association with neurophysiological changes in several psychiatric disorders, including depression and anxiety disorders.Normally, as integral components of the CAN, the PFC and amygdala mediate high-order autonomic control associated with cognitive perception and emotional responses, respectively, through the vagus nerve  and hypoLow HRV is associated with higher overall mortality, specifically heart mortality , and is considered a valid marker of heart disease ,20,43. AThe high comorbidity of stress-related psychiatric disorders and cardiovascular disease ,64,65,66A variety of studies, systematic reviews and meta-analyses have repeatedly shown that HRV displays good validity as a biomarker in psychiatry. Lower HRV and HRV reactivity has been associated with most psychiatric disorders , with higher symptom severity, as well as with specific endophenotypes ,77,78,79The Johns Hopkins Tripartite Model of Resistance, Resilience and Recovery suggests that individual ability for resistance to stress, rapid and effective rebound from stress and functional improvement after stress plays a crucial role in healthy adaptation, development of stress-related disorders and recovery treatment . ResearcAccording to Porges’ polyvagal theory ,90, autoThe Neurovisceral Integration Model is one of the most influential psychophysiological models addressing the interplay between CNS and somatic functioning (brain–body interaction). The model describes how a set of brain areas involved in cognitive, affective and autonomic regulation are related to HRV and cognitive performance . TherebyThe incorporation of autonomic (re)activity into a broader perspective on emotions, mental health and good cognitive and physical functioning should not only be used as a theoretical ground for further research, but also as a starting point for clinical applications . NeverthAdditional clinical intervention strategies could include more specific treatment alternatives, such as pharmacotherapy  and somatic afferent stimulation , to restore autonomic balance. Instead of exclusively targeting sympathetic activation as in the past, physicians should rather attempt to increase vagal tone. In particular, there has been increasing interest in treating a wide range of disorders with implanted pacemaker-like devices which stimulate the vagal afferent pathways for a broad range of diseases  in psychiatric disorders, b-adrenergic antagonists (β-blockers) have been suggested as adjunctive pharmacotherapy to successfully lower HR and increase HRV in anxiety but not in panic disorder and PTSD . HoweverFinally, the specific prognostic value of pre-exposure HR dynamics in the development of PTSD after trauma exposure is of crucial importance and is currently being pursued in prospective studies which suggest that an initially reduced HRV is a risk factor for PTSD . RelatedIn this respect, future studies focusing on the diurnal variability of autonomic stress reactivity and its role in the development of stress-related disorders and cardiac comorbidity are especially needed. In addition, seriously challenging conditions, despite their ethical problems, should be explored more thoroughly, particularly with respect to HRV responses and recovery, as well as to determine any therapeutic efficacy. Therefore, studies should focus more on unmedicated patients and/or consider a range of important exclusion criteria and factors that may influence results and conclusions when investigating HRV measures in healthy individuals and disease cohorts.The neurovisceral integration model proposes that altered stress system reactivity plays an important role in all major allostatic systems in the pathway from excessive stress to chronic disease . The undTherefore, HRV assessment, and especially more longitudinal monitoring by nonlinear methods, may improve our interpretations of autonomic dysregulation of HR dynamics and serve as a sensitive clinical biomarker which may even have potential prognostic value in future research into stress-related disorders. A full translation of findings on neuroautonomic heart control can only be achieved by nonlinear methods , as thesIndividual differences in stress (re)activity may vitally affect adaptive responses and may possibly explain individual differences in stress resilience and the progression of stress-related disorders. Therefore, a functional understanding of the brain–heart interaction requires considerable improvement through preclinical and prospective clinical research, as the role of the specific brain areas involved in central neuroautonomic dysregulation in response to specific stressors and stress-related disorders is still largely unclear. The further identification of biological factors that affect stress reactivity is, thus, of major importance for connecting cognitive, emotional, psychosocial and environmental stress factors with inter-individual variation in disease outcome. Since emotional and arousal circuitry largely overlaps with the CAN, HRV, especially nonlinear HR measures, could serve as suitable and fully translational biomarkers for stress system sensitivity, vulnerability and individual risk, with a potential much broader use in research and clinical practice.


Surgical voluntary medical male circumcision (VMMC) is a safe procedure; however, maintaining quality standards at scale, particularly during scale-up, is a challenge making ongoing quality management (QM) efforts essential. This study describes program quality measured by rates of adverse events (AEs) over four years of VMMC implementation in Namibia, compares AE rates over time, and discusses QM processes that contextualize AE trends and illustrate improvements in quality as the program matured. The International Training and Education Center for Health (I-TECH) assisted the Namibian Ministry of Health and Social Services (MoHSS) in expanding VMMC in three regions among boys and men over 10 years of age between January 2015 and September 2019.A comprehensive package of QM strategies was implemented by multi-disciplinary onsite teams with support from national and international technical advisors. Retrospective routine MoHSS data from the VMMC register, client forms, and monthly AE reports were collected during implementation in the three regions to assess the impact of QM interventions on AEs and to calculate the proportion of clients who experienced AEs over time. The proportion of clients who experienced an AE over time was compared using a Cochran-Armitage test for trend.Between January 2015 and September 2019, 40,336 clients underwent VMMC and 593 (1.5%) clients experienced a post-operative AE in the three supported regions. The AE rate was highest in the first quarter of clinical service delivery in each region  but declined over the implementation period as the program matured. This observed trend between program maturity and declining AE rates over time was significant (p < 0.001) when compared using a Cochran-Armitage test for trend.As the I-TECH-supported VMMC program matured, QM measures were introduced and routinized, and clinical quality improved over time with the rate of AEs decreasing significantly over the implementation period. Applying systematic and continuous QM processes and approaches across the continuum of VMMC services and considering local context can contribute to increased clinical safety. QM measures that are established in more mature program sites can be quickly adopted to respond to quality issues in program expansion sites. Voluntary medical male circumcision (VMMC) programs have been rapidly scaled, particularly in Southern and Eastern Africa, to meet World Health Organization (WHO) and Joint United Nations Programme on HIV and AIDS (UNAIDS) goals of 5 million VMMCs performed annually and the U.S. President’s Emergency Plan for AIDS Relief (PEPFAR) targets of 80% circumcision coverage of the eligible population , 2.When implemented in line with internationally established guidance, VMMC is a safe procedure . To mainQuality management (QM) comprises all activities designed to achieve and sustain high-quality outputs and encompasses quality assurance (QA), quality control (QC), and quality improvement (QI) approaches , 7. QA aThe WHO defined strategies for safeguarding VMMC quality, also incorporated into PEPFAR-funded program guidance, emphasize ensuring provider competence, monitoring and evaluating program outcomes including adverse events (AEs), and developing and implementing standard operating procedures and best practices for providing information and education to clients and communities , 11.Rates of AEs, especially during rapid program scale-up, are a key indicator of VMMC program quality given the critical importance of patient safety and good clinical outcomes in large scale VMMC efforts . AdverseThe objectives of this analysis are to (1) describe program quality measured by the rate of AEs that occurred over four years of program implementation in Namibia; (2) describe trends in AE rates over time; and (3) describe implemented QM processes to provide context to observed trends in AEs within Namibia and illustrate improvements in program quality as the VMMC program matured. This analysis builds on previously published work that provided a summary of the overall AE profile of Namibia’s VMMC program including AE type and timing, association of VMMC characteristics and AEs, as well as factors associated with AE severity .In 2010, the Namibian Ministry of Health and Social Services (MoHSS) launched its National Policy on Male Circumcision for HIV Prevention . To helpThe VMMC program was staffed by multi-disciplinary teams consisting of clinical, demand creation, and strategic information staff at the site level. The teams operated a main VMMC clinic integrated into the MoHSS hospital in each district, as well as regular outreach services at community-based primary healthcare (PHC) clinics and at other community institutions . All VMMC clinical staff completed theoretical and proficiency training including required completion of 20 VMMC procedures under direct supervision of an experienced and accredited supervisor prior to certification. The three regional site-teams were supported by a strategic leadership team based in Windhoek, Namibia, as well as Technical Advisor, Monitoring and Evaluation Advisor, and Senior Program Manager based in Seattle, USA. The Windhoek-based technical team provided close supervision and support to the site teams and undertook regular site visits that included onsite training, mentoring, and coaching on the implementation of QM measures. This multi-disciplinary team approach facilitated an environment in which service quality was prioritized, challenges were continuously identified, and contextually driven solutions were implemented.The program implemented a comprehensive package of QM measures described in Fig. Overall, the QM processes were implemented across three intervention levels: clinician facing interventions, client and community facing interventions, and interventions targeting program systems and processes. Clinician-facing activities safeguarded VMMC provider competency through training, development and implementation of job aides, and tools for continuous improvement of clinical service delivery. Client and community-facing activities focused on patient and caregiver education related to hygiene, pain management, and post-operative wound care, as well as provision of targeted wound care supplies and counseling. Systems-level QM measures focused on data review and management through implementation of new tools, new or modified clinical procedures, review of assessment and monitoring processes, and promotion of routine team-based data use to improve quality. This was supported by virtual weekly progress review and learning sessions which brought together site-level and above site-level team members.This study was conducted under a routine data use protocol approved by the U.S. Centers for Disease Control and Prevention (CDC) and the MoHSS. and received a non-research determination from the University of Washington institutional review board. In Namibia, adults < 18 years must obtain written approval from a parent or guardian for VMMC surgical procedures, no additional verbal or written consent from patients was not sought for this secondary analysis of the de-identified, aggregate data.For this analysis, we compiled routine monthly MoHSS AE reports (January 2015–September 2019) of individuals with moderate and severe AEs kept by clinicians at each site. MoHSS monthly program summary reports compiled from site-level VMMC registers and client forms by I-TECH’s site-level staff were used to establish the denominator of the number of VMMCs performed. The number of VMMCs performed served as the denominator in the calculation of AE rate as follow-up completion was nearly 100%. Both the AE line list data and the summary report data were analyzed at an aggregate level and disaggregated by location and program year.Internal program documents such as site visit reports, IQA and EQA reports, and emails and meeting notes were reviewed to identify QM activities implemented during the study period and to detail illustrative vignettes that demonstrate how quality issues were identified and resolved.The proportion of clients who experienced AEs were calculated using the compiled routine program data of the total clients who underwent VMMC during the implementation period as well as the total clients who experienced an AE (as identified by the line lists). The proportion of clients who experienced an AE over time was compared using a Cochran-Armitage test for trend. Confidence intervals (CI) (95% percentile) for AE rates by site calculated using Wilson estimates for trend analysis. This analysis was conducted using STATA 16.Two surgical circumcision techniques were used during the study period. Forceps-guided and dorsal slit VMMC were approved for clients ages 15 and older; for clients ages 10 through 14, only the dorsal slit VMMC procedure was approved. Clinicians determined the surgical type for clients aged 15 and above based on glans maturity. In Namibia, VMMC for clients aged 10–14 formed part of the 2010 Namibia National VMMC Policy and the dorsal slit procedure was authorized through an official policy circular issued by the MoHSS in October 2016.Generally, severe AEs require surgical intervention or hospitalization. Any AE not classified as severe but requiring medical intervention was considered moderate , 12. MilThe level of program maturity is represented by program duration.During the study period, 40,336 VMMCs were performed in three regions with 593 clients documented in the line lists as experiencing an AE Table . Over thThe AE rate was highest in the first quarter of clinical service delivery January-March 2015 in Oshana and Zambezi at 4.29 and 4.02 per 100 circumcisions performed and during the inception quarter of October-December 2017 in //Kharas at 11.49 per 100 circumcisions performed but subsequently consistently declined with increasing program maturation  action plans were applied to guide focused coaching, application of guidelines, and on-site training to improve routine VMMC program quality across the spectrum of VMMC program delivery finding that average program quality increased significantly  across CQI categories with larger gains in management and M&E over those observed in VMMC counselling or surgical skills . A previThere were several key concrete QM steps implemented as part of our program that VMMC or service delivery teams elsewhere may be able to implement. Starting in Oshana and Zambezi, and later in //Kharas, a multi-disciplinary team reviewed and discussed program data and AE rates on a weekly basis. Above-site technical advisors also made frequent in-person support visits to provide supportive supervision and mentorship and coaching. During those data reviews and site visits, conversations were held with the clinicians and clients and operations were observed to identify variations in quality standards. These reviews led to data-driven identification of problems, promoted joint team generation of possible solutions, and suggested specific new interventions for testing in support of continuous quality improvement.This study and findings are subject to several limitations. First, although implemented in three regions, overall absolute eligible target population numbers for VMMC are small, allowing for integration of intensive QM efforts using dedicated staffing and resources. The program had adequate technical assistance to step back from implementation and review data, identify solutions, and test change. This level of QM effort and resource application would likely not be sustainable on a national scale in less highly resourced regions. Second, these QM efforts were successful for the VMMC program but had limited direct benefit to the larger health systems in which the VMMC program was implemented. Future efforts should ensure that QM gains in a specific program will support horizontal approaches that strengthen other priority programs and the larger health system through capacity building, empowering local ownership, and developing cross-cutting quality management infrastructure . Third, Findings from this study lead to several programmatic recommendations that may further improve clinical service quality in Namibia’s VMMC program and are also applicable to other VMMC programs. Key findings and recommendations from this analysis include: (1) routinizing QM processes as the program matured aligned with an observed increase in clinical safety and improvement in program outcomes, (2) QM processes and approaches were applied across the continuum of VMMC services including client and community facing education and counselling, (3) QM efforts carefully considered and responded to the local context and were implemented using a multi-disciplinary team approach spanning multiple levels of the health system, (4) QM measures and experience established in more mature program sites can be applied to rapidly and efficiently resolve issues arising in program expansion sites with care taken to continue to be responsive to the specific sub-population and community needs in the expansion site. Patient safety and clinical outcomes are critical as VMMC programs continue to scale to meet ambitious national and international targets.


Diet-related inflammation is associated with adiposity. Obesity and inflammation in early life may have adverse health outcomes in later life; however, the socio-ecological predictors of a pro-inflammatory diet in childhood and adolescence are not well understood. This rapid scoping review aims to summarise the current state of research from observational studies investigating socio-ecological predictors  and their association with diet-associated inflammation and adiposity in children and adolescents.This scoping review will be conducted using the frameworks based on the Joanna Briggs Institute and Arksey and O’Malley and the Population, Concept and Context (PCC) mnemonic. Searches were conducted in OVID Medline, Cinahl and Embase, with adaptations as required. The piloted study selection process will utilise two reviewers for study selection, with reference lists checked for included studies. A third reviewer will moderate disagreements. Data will be extracted by one reviewer and calibrated by a second reviewer.The results will be reported using the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist and PRISMA-ScR flow diagram. The main findings will be synthesised into themes and concepts narratively. Tables and graphs will present frequencies, study details and categorical descriptions.This scoping review will provide an overview of the research conducted to date regarding predictors of diet-related inflammation in childhood and their associations with adiposity. Better understanding of the factors associated with a more inflammatory diet in childhood may be useful for clinicians and policy makers when designing and implementing health interventions. Childhood obesity has reached epidemic proportions worldwide –3 and haCritical phases of childhood development represent distinct periods during which physical alterations occur that may increase the prevalence of subsequent obesity . ImportaChronic inflammation, with persistently elevated levels of circulating pro-inflammatory biomarkers, is characteristic of obesity , 18 and Associations between dietary components as ecological predictors of diet-related inflammation are relatively well understood. For example, it is known that specific food components  and dietary patterns (Western-style diet) are associated with elevated biological inflammatory markers in children and adolescents . However®) [™) [™) [When assessing diet as an environmental factor associated with inflammation in children, several indices have been used to score the inflammatory potential of the diet, including the Dietary Inflammatory Index (DII®) , 30 and ®) [™) ; the Chi [™) [™) , 28 and  [™) [™) . The DII [™) [™) . Higher  [™) [™) , 28, 32  [™) [™) . A recen [™) [™) , suggestPrediction research is useful to help forecast future disease occurrence. This includes predictor finding studies (of risk factors) and predictor modelling studies , 36. TheTherefore, the aims of this scoping review are to:Summarise the current state of research and gaps in the literature investigating the association between dietary inflammation scores and adiposity in children and adolescents in observational studies;Summarise the current research reporting associations between socio-ecological predictors (risk factors), or prediction models, of dietary inflammation in childhood and adolescence, measured by dietary inflammation scores and associations with adiposity in observational studies; andDescribe whether there is any variation of risk at different childhood ages  of a more pro-inflammatory diet associated with adiposity.The objective of this review is to subsequently inform future research investigating predictors and prediction models of dietary inflammation and obesity in children in observational studies. The feasibility of prediction modelling from potential candidate predictors will also be explored .The scoping review methods were developed using the Joanna Briggs Institute’s (JBI) updated guidance on scoping reviews , incorpoTo formulate the key factors and criteria being investigated in this review, the Population, Concept and Context (PCC) mnemonic was used as recommended by JBI .The target population consists of children and adolescents ≥2 years and <19 years of age based on World Health Organization definitions , 50. TheThe breadth of inquiry will include studies with outcomes in the phenomena of interest; predictors of diet-related inflammation and adiposity. ‘Predictors’ in this study refers to risk factor variables in relation to a more pro-inflammatory diet and their associations with adiposity, including socio-ecological predictors: biological, familial or environmental. Socio-ecological predictors will be adapted from ecological factors in childhood obesity described by Davison and Birch (2001) and matched to potential cohort data and include:Child characteristics include sex, age, adiposity measures and risk factors: sedentary behaviour, physical activity;Parental styles and familial characteristics include parental dietary intake, weight status, activity patterns, smoking and alcohol intake;Parental demographic characteristics include ethnicity, work hours, leisure time, socio-economic status and education level;Chronobiological characteristics include meal timing and sleep.Specific dietary factors (food groups and nutrients) will not be the focus as these associations with the C-DII are comparatively well explored in contrast to wider socio-ecological risk factors .As an exploratory analysis, studies reporting prediction modelling of dietary-related inflammation also is of interest. These include studies developing new prediction models or validating or updating existing prediction models . ConceptThe context of this scoping review is in observational studies, defined as studies with either cohort, case-control or cross-sectional designs  that wil1. What is known from the current published literature in observational studies about the association between a more inflammatory diet, measured by higher dietary inflammation scores, and association with adiposity in childhood and adolescence?2. What is known from the current published literature in observational studies about socio-ecological predictors of a more inflammatory diet, measured by higher dietary inflammation scores, and their association with childhood and adolescent adiposity?3. What is known from the current published literature about the variation in risk of a more inflammatory diet at different stages of childhood and adolescence  identified from the primary research questions?4. What is known from the current published literature about the variation in risk of a more inflammatory diet and association with chronobiological factors ?5. What is known from the current published literature about prediction modelling developed in observational studies, investigating candidate predictors in determining the risk of dietary inflammation in childhood and adolescence?The search strategy was developed primarily by one reviewer with input from the research team and a research librarian. Variations were discussed and agreed by the reviewers and were documented. As the search process is recommended to be iterative, there is provision to allow modification of keywords, search terms and information sources as the reviewers become increasingly familiar with the literature , 40.The databases to be searched were OVID Medline, Cinahl and Embase. Initial scoping searches were piloted in OVID Medline and adapted as required for other databases. The search results were documented and the full search strategy of one major database (OVID Medline) is provided.Where databases allowed, limits were used to restrict studies to ‘human’, ‘title and abstract’ though this was trialled in each database to determine impact on the output specificity and sensitivity. The search strategy was piloted and refined before final run and modified minimally as required for each database. The search strategy was finalised after trialling using a combination of key words and phrases, synonyms and controlled vocabulary  .post-hoc as familiarity with the literature increases [The inclusion and exclusion criteria for the searches are matched to the PCC . These cncreases  and on dncreases . Title aThe search outputs will be combined within Endnote . The citations will be uploaded to Covidence systematic review software  for screCritical appraisal of the selected studies will not be conducted as it is not required to meet the specific aims of this scoping review .Extracted information will be synthesised using a piloted electronic data extraction table in Microsoft Excel, using the first 4 studies retrieved  and reviData underlying the findings will be made available at the time of publication as part of the manuscript or included as supplemental material. Data will be presented in tables/charts, supported by a narrative summary discussing the findings in relation to the objectives of the review.The final studies selected will undergo syntheses into themes to extract and record the relevant findings for thematic arrangement into outcome domains and comparative overview. Categorisation into the outcome domains and themes will utilise an iterative approach to guide conceptualisation of the thematic structure, undertaken by one reviewer and then referred to the review team for consensus . These mIf authors need to be contacted for clarification or to request additional data, it will be documented and reported in the review.The following data will be extracted:Study details: Author(s), publication year, study location.Study methodology: Aims, study type, methodology (eligibility criteria for participants), comparator, duration, study population/setting , outcome measures. Additionally, for prediction modelling studies this information will be recorded: key study dates , candidate predictors and how/when they were measured, model development methodology, model performance, discrimination, calibration, validation, sensitivity, specificity, predictive capacity.Results:Number of participants/sample size, participant characteristics , missing data, mean follow up/length of investigation, number of outcome events, loss to follow up, predictors/risk factors identified.Additionally, for predictor finding studies hazard ratios (HR), risk ratios (RR) or odds ratios (OR) from the most fully adjusted model for the highest versus the lowest exposure categories or levels and corresponding 95% Confidence Intervals (CIs) for exposure categories, or P-values, and authors’ conclusions will be reported.2 values, unadjusted associations between candidate predictors and outcome, prediction model performance measures (with CIs), and proposed use of the prediction model will be reported.Additionally, for prediction modelling studies: type of study , number of participants/sample size, final model predictors, goodness of fit test for models, probabilities , sensitivity, specificity, accuracy, RMSE, prediction intervals, RTo ensure accurate and transparent reporting, each stage of the review will be reported using the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist . A narraFirst, the search results will be presented narratively and in a PRISMA-ScR flow diagram to present an overview of the identification, screening, assessment of eligibility and selection processes . The maiDiscussion of the results of the ensuing rapid scoping review will be guided by the PRISMA ScR checklist and will include a summary of evidence as described in Stage 5, a discussion of the limitations and strengths of the review, and concluding remarks to interpret the results, implications and future directions.Understanding the predictors of childhood dietary-related inflammation and its association with childhood obesity is important in the development of public health prevention strategies to reduce the burden that obesity places on individuals and society, including health trajectories and outcomes into adolescence and adulthood . This reS1 Table(PDF)Click here for additional data file.