Monitorización de la glucemia en el paciente crítico adulto: tipo de muestra y método de análisis. Revisión sistemática y metanálisis / Blood glucose monitoring in critically ill adult patients: Type of sample and method of analysis. Systematic review and meta-analysis

IntroducciónLa guía clínica para el manejo de la sepsis recomienda usar muestras de sangre arterial para el control glucémico. Un estudio multicéntrico en 86 unidades de cuidados intensivos españolas reveló que el 85,4% de estas utilizaban punción capilar.ObjetivoAnalizar la fiabilidad de la glucemia comparando diferentes muestras sanguíneas (arterial, venosa, capilar) e instrumentos (glucómetros, gasómetros, laboratorio central). Secundariamente, estimar el efecto de variables confusoras y el rendimiento de los instrumentos de medición determinados por las diferentes normas de calidad.MetodologíaRevisión sistemática y metanálisis con búsqueda en las bases de datos PubMed, CINAHL y Embase en septiembre-2021 y septiembre-2022, sin límites temporales ni idiomáticos. Fuentes de literatura gris: DART-Europe, OpenGrey y Google Académico. Resultados resumidos mediante síntesis cualitativa (descripción de resultados, características de los estudios) y cuantitativa (metanálisis para evaluar la diferencia de medias estandarizadas). Calidad metodológica de artículos evaluada con Quality Assessment of Diagnostic Accuracy Studies-2. Protocolo: https://osf.io/ DOI 10.17605/OSF.IO/T8KYP.ResultadosSe incluyeron un total de 32 artículos y 5.451 pacientes. No se obtuvieron discrepancias entre muestras arteriales con glucómetro vs. laboratorio (sesgo [IC95%]: 0,01 [−0,12 a 0,14] mg/dL). En cambio, muestras arteriales con gasómetro sí sobreestimaron de forma significativa (sesgo [IC95%]: 0,12 [0,01 a 0,24] mg/dL). La misma tendencia presentan capilares con glucómetro, aunque no de forma significativa (sesgo [IC95%]: 0,07 [−0,02 a 0,15] mg/dL). Hay discrepancia entre los estudios sobre el efecto del hematocrito y el equilibrio ácido-base. El mayor consenso se da en la poca concordancia del glucómetro con muestras capilares vs. laboratorio en presencia de shock y soporte vasopresor, situación de fallo renal o durante el tratamiento con vitamina C.Conclusiones... (AU)

IntroductionThe clinical guideline for the management of sepsis recommends using arterial blood samples for glycaemic control. A multicentre study in 86 Spanish intensive care units revealed that 85.4% of these used capillary puncture.ObjectiveTo analyse the reliability of glycaemia by comparing different blood samples (arterial, venous, capillary) and instruments (glucometers, gasometers, central laboratory). Secondarily, to estimate the effect of confounding variables and the performance of measuring instruments as determined by different quality standards.MethodologySystematic review and meta-analysis with search in PubMed, CINAHL and Embase databases in September-2021 and September-2022, with no time or language limits. Grey literature sources: DART-Europe, OpenGrey and Google Scholar. Results summarised by qualitative (description of results, study characteristics) and quantitative (meta-analysis to assess standardised mean difference) synthesis. Methodological quality of articles assessed with Quality Assessment of Diagnostic Accuracy Studies-2. Protocol: https://osf.io/ DOI 10.17605/OSF.IO/T8KYP.ResultsA total of 32 articles and 5451 patients were included. No discrepancies were obtained between arterial glucometer vs. laboratory samples (bias [95%CI]: 0.01 [−0.12 to 0.14] mg/dL). In contrast, arterial samples with a gasometer did significantly overestimate (bias [95%CI]: 0.12 [0.01 to 0.24] mg/dL). The same trend is seen in capillaries with a glucometer, although not significantly (bias [95%CI]: 0.07 [−0.02 to 0.15] mg/dL). There is discrepancy between studies on the effect of haematocrit and acid-base balance. The greatest consensus is on the poor agreement of glucometer with capillary vs. laboratory samples in the presence of shock and vasopressor support, renal failure or during vitamin C treatment.Conclusions... (AU)

The path from task-specific to general purpose artificial intelligence for medical diagnostics: A bibliometric analysis.

Artificial intelligence (AI) has revolutionized many fields, and its potential in healthcare has been increasingly recognized. Based on diverse data sources such as imaging, laboratory tests, medical records, and electrophysiological data, diagnostic AI has witnessed rapid development in recent years. A comprehensive understanding of the development status, contributing factors, and their relationships in the application of AI to medical diagnostics is essential to further promote its use in clinical practice. In this study, we conducted a bibliometric analysis to explore the evolution of task-specific to general-purpose AI for medical diagnostics. We used the Web of Science database to search for relevant articles published between 2010 and 2023, and applied VOSviewer, the R package Bibliometrix, and CiteSpace to analyze collaborative networks and keywords. Our analysis revealed that the field of AI in medical diagnostics has experienced rapid growth in recent years, with a focus on tasks such as image analysis, disease prediction, and decision support. Collaborative networks were observed among researchers and institutions, indicating a trend of global cooperation in this field. Additionally, we identified several key factors contributing to the development of AI in medical diagnostics, including data quality, algorithm design, and computational power. Challenges to progress in the field include model explainability, robustness, and equality, which will require multi-stakeholder, interdisciplinary collaboration to tackle. Our study provides a holistic understanding of the path from task-specific, mono-modal AI toward general-purpose, multimodal AI for medical diagnostics. With the continuous improvement of AI technology and the accumulation of medical data, we believe that AI will play a greater role in medical diagnostics in the future.

[The impact of primary data quality and interoperability on the analysis of real-world data]. / Die Auswirkungen von Primärdatenqualität und -interoperabilität auf Analysen von Real-World-Daten.

Real-world data is increasingly becoming the focus of healthcare research in the context of digitization. The timely availability of large amounts of data gives hope that research questions can be answered quickly without additional data collection and that a direct benefit for the care of people can be achieved. Especially in acute care situations, such as heat waves or a pandemic, this can be crucial. But real-world data depend quite significantly on the quality and intent of data collection. It is also influenced by determinations on semantic and syntactic standards that are made for primary data - often considering different use cases. In the context of different initiatives on national and international levels, a holistic view on data collection and evaluation and a regular feedback mechanism between data evaluation and specifications for the collection should be established. By including requirements for secondary data evaluation in the definition processes for data collection, the informative value of the data for research can be increased in the long term.In this discussion paper, the activities for standardized data collection in the context of the digitization initiatives and the corresponding European approaches are first presented. After outlining the effects of these activities on the possibilities and difficulties of data consolidation for the analysis of real-world data, the article calls for an ongoing discourse between the different areas.

Taste shaped the use of botanical drugs.

The perception of taste and flavour (a combination of taste, smell, and chemesthesis), here also referred to as chemosensation, enables animals to find high-value foods and avoid toxins. Humans have learned to use unpalatable and toxic substances as medicines, yet the importance of chemosensation in this process is poorly understood. Here, we generate tasting-panel data for botanical drugs and apply phylogenetic generalised linear mixed models to test whether intensity and complexity of chemosensory qualities as well as particular tastes and flavours can predict ancient Graeco-Roman drug use. We found chemosensation to be strongly predictive of therapeutic use: botanical drugs with high therapeutic versatility have simple yet intense tastes and flavours, and 21 of 22 chemosensory qualities predicted at least one therapeutic use. In addition to the common notion of bitter tasting medicines, we also found starchy, musky, sweet, and soapy drugs associated with versatility. In ancient Greece and Rome, illness was thought to arise from imbalance in bodily fluids or humours, yet our study suggests that uses of drugs were based on observed physiological effects that are often consistent with modern understanding of chemesthesis and taste receptor pharmacology.

In ancient times people used trial and error to identify medicinal plants as being effective. Later, diseases were believed to arise from imbalances in body fluids (or 'humours'), and botanical drugs were thought to restore this balance through the power of their taste. Modern science rejects this theory but does recognise the importance of chemosensation ­ our sensitivity to chemicals through taste and smell. These senses evolved in humans to help us seek out nutrients and avoid toxins and may also have guided the ancient uses of botanical drugs. There are many records of historical medicinal plant use and ailments, which makes it possible to explore possible relationships between therapeutic uses of botanical drugs and their chemosensory qualities. To investigate if therapeutic uses of botanical drugs could indeed be predicted by taste and flavour, Leonti, Baker et al. collected 700 botanical drugs identified in an ancient text, named De Materia Medica, which dates back to the 1^st century CE. The researchers asked volunteer tasters to classify the botanical drugs using 22 taste descriptions, such as bitter, aromatic, burning/hot, and fresh/cooling. The volunteers were also asked to score the strength of these tastes. Leonti, Baker et al. then used statistical modelling to see if the participant's taste descriptions could be used to predict the therapeutic uses of the drugs identified in the ancient text. This revealed that of the 46 therapeutic indications described in the text, 45 showed significant associations with at least one taste quality. Botanical drugs with stronger and simpler tastes tended to be used for a wider range of therapeutic indications. This suggests that chemosensation influenced therapeutic expectations in ancient, prescientific medicine. The study of Leonti, Baker et al. brings ancient medicine to life, offering valuable insights into the chemosensory aspects of medicinal plants and their potential applications in modern medicine. A next step would be to explore whether these insights could have relevance to modern science.

Reducing implicit bias in the neurosurgery application and interview process: a single-institution experience.

OBJECTIVE: The neurosurgical match is a challenging process for applicants and programs alike. Programs must narrow a wide field of applicants to interview and then determine how to rank them after limited interaction. To streamline this, programs commonly screen applicants using United States Medical Licensing Examination (USMLE) Step scores. However, this approach removes nuance from a consequential decision and exacerbates existing biases. The primary objective of this study was to demonstrate the feasibility of effecting minor modifications to the residency application process, as the authors have done at their institution, specifically by reducing the prominence of USMLE board scores and Alpha Omega Alpha (AΩA) status, both of which have been identified as bearing racial biases. METHODS: At the authors' institution, residents and attendings holistically reviewed applications with intentional redundancy so that every file was reviewed by two individuals. Reviewers were blinded to applicants' photographs and test scores. On interview day, the applicant was evaluated for their strength in three domains: knowledge, commitment to neurosurgery, and integrity. For rank discussions, applicants were reviewed in the order of their domain scores, and USMLE scores were unblinded. A regression analysis of the authors' rank list was made by regressing the rank list by AΩA status, Step 1 score, Step 2 score, subinternship, and total interview score. RESULTS: No variables had a significant effect on the rank list except total interview score, for which a single-point increase corresponded to a 15-position increase in rank list when holding all other variables constant (p < 0.05). CONCLUSIONS: The goal of this holistic review and domain-based interview process is to mitigate bias by shifting the focus to selected core qualities in lieu of traditional metrics. Since implementation, the authors' final rank lists have closely reflected the total interview score but were not significantly affected by board scores or AΩA status. This system allows for the removal of known sources of bias early in the process, with the aim of reducing potential downstream effects and ultimately promoting a final list that is more reflective of stated values.

Development of novel composite data quality scores to evaluate facility-level data quality in electronic data in Kenya: a nationwide retrospective cohort study.

BACKGROUND: In this evaluation, we aim to strengthen Routine Health Information Systems (RHIS) through the digitization of data quality assessment (DQA) processes. We leverage electronic data from the Kenya Health Information System (KHIS) which is based on the District Health Information System version 2 (DHIS2) to perform DQAs at scale. We provide a systematic guide to developing composite data quality scores and use these scores to assess data quality in Kenya. METHODS: We evaluated 187 HIV care facilities with electronic medical records across Kenya. Using quarterly, longitudinal KHIS data from January 2011 to June 2018 (total N = 30 quarters), we extracted indicators encompassing general HIV services including services to prevent mother-to-child transmission (PMTCT). We assessed the accuracy (the extent to which data were correct and free of error) of these data using three data-driven composite scores: 1) completeness score; 2) consistency score; and 3) discrepancy score. Completeness refers to the presence of the appropriate amount of data. Consistency refers to uniformity of data across multiple indicators. Discrepancy (measured on a Z-scale) refers to the degree of alignment (or lack thereof) of data with rules that defined the possible valid values for the data. RESULTS: A total of 5,610 unique facility-quarters were extracted from KHIS. The mean completeness score was 61.1% [standard deviation (SD) = 27%]. The mean consistency score was 80% (SD = 16.4%). The mean discrepancy score was 0.07 (SD = 0.22). A strong and positive correlation was identified between the consistency score and discrepancy score (correlation coefficient = 0.77), whereas the correlation of either score with the completeness score was low with a correlation coefficient of -0.12 (with consistency score) and -0.36 (with discrepancy score). General HIV indicators were more complete, but less consistent, and less plausible than PMTCT indicators. CONCLUSION: We observed a lack of correlation between the completeness score and the other two scores. As such, for a holistic DQA, completeness assessment should be paired with the measurement of either consistency or discrepancy to reflect distinct dimensions of data quality. Given the complexity of the discrepancy score, we recommend the simpler consistency score, since they were highly correlated. Routine use of composite scores on KHIS data could enhance efficiencies in DQA at scale as digitization of health information expands and could be applied to other health sectors beyondHIV clinics.

Effects of blended learning training for oncology physicians to advise their patients about complementary and integrative therapies: results from the multicenter cluster-randomized KOKON-KTO trial.

BACKGROUND: Many oncology physicians are confronted with the topic of complementary and integrative medicine (CIM) by cancer patients. This study examined whether a blended learning (e-learning and a workshop) to train oncology physicians in providing advice on CIM therapies to their cancer patients, in addition to distributing an information leaflet about reputable CIM websites, had different effects on physician-reported outcomes in regard to consultations compared with only distributing the leaflet. METHODS: In a multicenter, cluster-randomized trial, 48 oncology physicians were randomly allocated to an intervention group (CIM consultation and an information leaflet) or a control group (information leaflet only). After the training, the oncology physicians conducted 297 consultations with their cancer patients. Measurements were assessed at oncology physician, physician-patient-interaction (measured by external reviewers), and patient levels. This analysis focused on the physician outcomes of stress reaction and perceived consultation skill competency. In addition, qualitative interviews were conducted with a subsample of oncology physicians who experienced both, the intervention and control condition. RESULTS: The oncology physicians in the intervention group showed a lower stress reaction in all measured dimensions after CIM consultations than those in the control group. There was no significant difference between oncology physicians in the intervention and control groups regarding the perceived consultation skill competency (overburden: intervention 1.4 [95% CI: 0.7;2.1]; control 2.1 [95% CI: 1.4;2.7], tension: 1.3 [95% CI: 0.7;2.0] vs. 1.9 [95% CI: 1.3;2.5], and discomfort with consultation situations: 1.0 [95% CI: 0.4;1.7]; vs. 1.7 [95% CI: 1.2;2.3]). The qualitative data showed that only providing the leaflet seemed impersonal to oncology physicians, while the training made them feel well prepared to conduct a full conversation about CIM and provide the information leaflet. CONCLUSIONS: In our exploratory study providing structured CIM consultations showed positive effects on the perceived stress of oncology physicians, and the training was subjectively experienced as an approach that improved physician preparation for advising cancer patients about CIM, however no effects regarding perceived consultation skill competency were found. TRIAL REGISTRATION: The trial registration number of the KOKON-KTO study is DRKS00012704 in the German Clinical Trials Register (Date of registration: 28.08.2017).

What are the perspectives of adults aged 18-40 living with type 2 diabetes in urban settings towards barriers and opportunities for better health and well-being: a mixed-methods study.

OBJECTIVES: Delivered as part of the global assessment of diabetes in urban settings, this study explores different aspects of living with type 2 diabetes, for adults aged 18-40. Primary questions were as follows: (1) can we identify subgroups of adults under 40 years old sharing specific perspectives towards health, well-being and living with type 2 diabetes and (2) do these perspectives reveal specific barriers to and opportunities for better type 2 diabetes prevention and management and improved well-being? DESIGN: The study employed a mixed-method design with data collected through demographic questionnaires, Q-sort statement sorting exercises, focus groups discussions and individual interviews. SETTING: Primary care across Greater Manchester, UK. PARTICIPANTS: Those aged between 18 and 40, with a confirmed type 2 diabetes diagnosis, and living in Greater Manchester were eligible to participate. A total of 46 people completed the Q-sort exercise and 43 were included in the final analysis. Of those, 29 (67%) identified as female and 32 (75%) as white. Most common time since diagnosis was between 5 and 10 years. RESULTS: The Q-sort analysis categorised 35 of the 43 participants (81%) into five subgroups. Based on average statement sorts for each subgroup, perspectives were characterised as: (1) stressed and calamity coping (n=13), (2) financially disadvantaged and poorly supported (n=12), (3) well-intentioned but not succeeding (n=5), (4) withdrawn and worried (n=2) and (5) young and stigmatised (n=3). Holistic analysis of our qualitative data also identified some common issues across these subgroups. CONCLUSIONS: Adults under 40 with type 2 diabetes are not a homogeneous group, but fall into five identifiable subgroups. They also experience issues specific to this age group that make it particularly difficult for them to focus on their own health. More tailored support could help them to make the necessary lifestyle changes and manage their type 2 diabetes better.

A survey of Australian women's digital media usage in pregnancy and labour and birth.

BACKGROUND: Given the rapid growth of digital media resources, it is worth exploring childbearing women's use of digital media to address their information needs. The aim of this study was to explore the use of digital media during pregnancy and birth in the local population of Western Victorian women in Melbourne, Australia. METHODS: A descriptive exploratory approach was used. An online survey consisted of both quantitative and qualitative questions to identify and measure digital media use in pregnancy and the birthing period. Descriptive statistics and Pearson Chi-square test were used to analyse the quantitative data, while content analysis was used to analyse the qualitative data. RESULTS: Digital media has become an integral part of the experience in pregnancy with increasing growth of digital media in labour. The most used medium for digital media use was pregnancy applications, followed by websites, social media, YouTube, podcasts, online discussion forums and lastly, labour applications. Information seeking was the main reason for using digital media, and two main themes emerged from the qualitative data; 'connection with others for social support and reassurance' and 'information seeking and providing to assist decision making and providing reassurance'. CONCLUSION: This study highlights the need for future midwifery practice to include digital media sources in antenatal education and care. There is a need for healthcare institutions to improve digital media technology to meet the needs of women. This is crucial as digital media is constantly evolving, and as healthcare providers, we need to integrate digital media with healthcare services.

Enhancing Smart Agriculture by Implementing Digital Twins: A Comprehensive Review.

Digital Twins serve as virtual counterparts, replicating the characteristics and functionalities of tangible objects, processes, or systems within the digital space, leveraging their capability to simulate and forecast real-world behavior. They have found valuable applications in smart farming, facilitating a comprehensive virtual replica of a farm that encompasses vital aspects such as crop cultivation, soil composition, and prevailing weather conditions. By amalgamating data from diverse sources, including soil, plants condition, environmental sensor networks, meteorological predictions, and high-resolution UAV and Satellite imagery, farmers gain access to dynamic and up-to-date visualization of their agricultural domains empowering them to make well-informed and timely choices concerning critical aspects like efficient irrigation plans, optimal fertilization methods, and effective pest management strategies, enhancing overall farm productivity and sustainability. This research paper aims to present a comprehensive overview of the contemporary state of research on digital twins in smart farming, including crop modelling, precision agriculture, and associated technologies, while exploring their potential applications and their impact on agricultural practices, addressing the challenges and limitations such as data privacy concerns, the need for high-quality data for accurate simulations and predictions, and the complexity of integrating multiple data sources. Lastly, the paper explores the prospects of digital twins in agriculture, highlighting potential avenues for future research and advancement in this domain.

Advancing socioecological mental health promotion intervention: A mixed methods exploration of Phase 1 Agenda Gap findings.

Introduction: Protecting and promoting the mental health of youth under 30 years of age is a priority, globally. Yet investment in mental health promotion, which seeks to strengthen the determinants of positive mental health and wellbeing, remains limited relative to prevention, treatment, and recovery. The aim of this paper is to contribute empirical evidence to guide innovation in youth mental health promotion, detailing the early outcomes of Agenda Gap, an intervention centering youth-led policy advocacy to influence positive mental health for individuals, families, communities and society. Methods: Leveraging a convergent mixed methods design, this study draws on data from n = 18 youth (ages 15 to 17) in British Columbia, Canada, who contributed to pre- and post-intervention surveys and post-intervention qualitative interviews following their participation in Agenda Gap from 2020-2021. These data are supplemented by qualitative interviews with n = 4 policy and other adult allies. Quantitative and qualitative data were analyzed in parallel, using descriptive statistics and reflexive thematic analysis, and then merged for interpretation. Results: Quantitative findings suggest Agenda Gap contributes to improvements in mental health promotion literacy as well as several core positive mental health constructs, such as peer and adult attachment and critical consciousness. However, these findings also point to the need for further scale development, as many of the available measures lack sensitivity to change and are unable to distinguish between higher and lower levels of the underlying construct. Qualitative findings provided nuanced insights into the shifts that resulted from Agenda Gap at the individual, family, and community level, including reconceptualization of mental health, expanded social awareness and agency, and increased capacity for influencing systems change to promote positive mental health and wellbeing. Discussion: Together, these findings illustrate the promise and utility of mental health promotion for generating positive mental health impacts across socioecological domains. Using Agenda Gap as an exemplar, this study underscores that mental health promotion programming can contribute to gains in positive mental health for individual intervention participants whilst also enhancing collective capacity to advance mental health and equity, particularly through policy advocacy and responsive action on the social and structural determinants of mental health.

Digital Health Data Quality Issues: Systematic Review.

BACKGROUND: The promise of digital health is principally dependent on the ability to electronically capture data that can be analyzed to improve decision-making. However, the ability to effectively harness data has proven elusive, largely because of the quality of the data captured. Despite the importance of data quality (DQ), an agreed-upon DQ taxonomy evades literature. When consolidated frameworks are developed, the dimensions are often fragmented, without consideration of the interrelationships among the dimensions or their resultant impact. OBJECTIVE: The aim of this study was to develop a consolidated digital health DQ dimension and outcome (DQ-DO) framework to provide insights into 3 research questions: What are the dimensions of digital health DQ? How are the dimensions of digital health DQ related? and What are the impacts of digital health DQ? METHODS: Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a developmental systematic literature review was conducted of peer-reviewed literature focusing on digital health DQ in predominately hospital settings. A total of 227 relevant articles were retrieved and inductively analyzed to identify digital health DQ dimensions and outcomes. The inductive analysis was performed through open coding, constant comparison, and card sorting with subject matter experts to identify digital health DQ dimensions and digital health DQ outcomes. Subsequently, a computer-assisted analysis was performed and verified by DQ experts to identify the interrelationships among the DQ dimensions and relationships between DQ dimensions and outcomes. The analysis resulted in the development of the DQ-DO framework. RESULTS: The digital health DQ-DO framework consists of 6 dimensions of DQ, namely accessibility, accuracy, completeness, consistency, contextual validity, and currency; interrelationships among the dimensions of digital health DQ, with consistency being the most influential dimension impacting all other digital health DQ dimensions; 5 digital health DQ outcomes, namely clinical, clinician, research-related, business process, and organizational outcomes; and relationships between the digital health DQ dimensions and DQ outcomes, with the consistency and accessibility dimensions impacting all DQ outcomes. CONCLUSIONS: The DQ-DO framework developed in this study demonstrates the complexity of digital health DQ and the necessity for reducing digital health DQ issues. The framework further provides health care executives with holistic insights into DQ issues and resultant outcomes, which can help them prioritize which DQ-related problems to tackle first.

Effectiveness of four deconstructive meditative practices on well-being and self-deconstruction: study protocol for an exploratory randomized controlled trial.

INTRODUCTION: The efficacy of interventions based on mindfulness and compassion has been demonstrated in both clinical and general population, and in different social contexts. These interventions include so-called attentional and constructive meditation practices, respectively. However, there is a third group, known as deconstructive meditation practices, which has not been scientifically studied. Deconstructive practices aim to undo maladaptive cognitive patterns and generate knowledge about internal models of oneself, others and the world. Although there are theoretical and philosophical studies on the origin of addiction to the self or on the mechanisms of action associated with the deconstruction of the self, there are no randomized controlled trials evaluating these techniques in either a healthy population or clinical samples. This study aims to evaluate the effect of three deconstructive techniques by comparing them to mindfulness in the general population. METHODS AND ANALYSIS: A randomized controlled clinical trial will be conducted with about 240 participants allocated to four groups: (a) mindful breathing, (b) prostrations, according to Tibetan Buddhist tradition; (c) the Koan Mu, according to Zen Buddhist tradition; and (d) the mirror exercise, according to Toltec tradition. The primary outcome will be the qualities of the non-dual experience and spiritual awakening, measured by the Nondual Embodiment Thematic Inventory, assessed at pre- and post-treatment and at 3- and 6-month follow-ups. Other outcomes will be mindfulness, happiness, compassion, affectivity and altered state of consciousness. Quantitative data will be compared using mixed-effects linear regression models, and qualitative data will be analysed through thematic analysis and using the constant comparative method from grounded theory. ETHICS AND DISSEMINATION: Approval was obtained from the Research Ethics Committee of Aragon, Spain. The results will be submitted to peer-reviewed specialized journals, and brief reports will be sent to participants on request. TRIAL REGISTRATION: ClinicalTrials.gov NCT05317754. Registered on August 2,2022.

Sistema de avaliação de testes psicológicos: histórias contadas e não contadas / Psychological test evaluation system: stories told and untold / Sistema de evaluación de tests psicológicos: historias contadas y no contadas

O Sistema de Avaliação de Testes Psicológicos (SATEPSI) recebeu notoriedade entre brasileiros e estrangeiros por oferecer um complexo sistema de qualificação dos testes psicológicos, pouco visto em âmbito mundial. Sua elaboração dependeu de uma autarquia, que o financiou, normatizou e o mantém, mas também de pesquisadores docentes de avaliação psicológica, que trouxeram a expertise da área para que houvesse o pleno estabelecimento de seus parâmetros. Passadas duas décadas de seu lançamento, o SATEPSI foi tema de artigos, capítulos, lives e diálogos digitais, nos quais foram destaque, de modo geral, as Resoluções do Conselho Federal de Psicologia, que o normatiza, e seus impactos para a área de avaliação psicológica - como, por exemplo, o aumento do número de pesquisas e de testes brasileiros qualificados. O que se pretende neste artigo é mencionar sua construção, à luz dos autores que vivenciaram o SATEPSI em funções e tempos distintos. Atenção especial será dada aos Métodos Projetivos, cuja história ainda é pouco revelada.(AU)

The system to evaluate psychological tests (Satepsi) received notoriety among Brazilians and foreigners for offering a complex system of qualification of psychological tests, which is rarely seen worldwide. Its development depended on an autarchy (which financed, standardized, and maintains it) and on researchers teaching psychological assessment, who brought their expertise to the area so its parameters could be fully established. After two decades of its launch, Satepsi was the subject of articles, chapters, lives, and digital dialogues, which usually highlighted the Resolutions of the Federal Council of Psychology that normatize psychological evaluation and their impacts, such as the increase in the number of qualified Brazilian tests. This study aims to mention its construction in the light of the authors who experienced Satepsi in different functions and times, giving special attention to Projective Methods, whose history remains to be shown.(AU)

El Sistema de Evaluación de Tests Psicológicos (SATEPSI) ganó notoriedad entre los brasileños y los extranjeros por ofrecer un complejo sistema de calificación de los tests psicológicos, poco frecuente a nivel mundial. Su elaboración dependió de una autarquía, que lo financió, lo estandarizó y lo mantiene, pero también de investigadores docentes de evaluación psicológica, que trajeron la experiencia del área para que hubiera el pleno establecimiento de sus parámetros. Tras dos décadas de su lanzamiento, SATEPSI fue tema de artículos, capítulos, en directo y diálogos digitales, en los cuales destacaron, de modo general, las Resoluciones del Consejo Federal de Psicología que lo normatiza y sus impactos para el área de evaluación psicológica, como el aumento del número de investigaciones y de pruebas brasileñas calificadas. Lo que se pretende en este artículo es mencionar su construcción, a la luz de los autores que vivieron el SATEPSI en funciones y tiempos distintos. Se prestará especial atención a los métodos proyectivos cuya historia aún no se ha revelado.(AU)

Routine use of DHIS2 data: a scoping review.

BACKGROUND: In regard to health service planning and delivery, the use of information at different levels in the health system is vital, ranging from the influencing of policy to the programming of action to the ensuring of evidence-informed practices. However, neither ownership of, nor access to, good quality data guarantees actual use of these data. For information to be used, relevant data need to be collected, processed and analysed in an accessible format. This problem of underused data, and indeed the absence of data use entirely, is widespread and has been evident for decades. The DHIS2 software platform supports routine health management for an estimated 2.4 billion people, in over 70 countries worldwide. It is by far the largest and most widespread software for this purpose and adopts a holistic, socio-technical approach to development and implementation. Given this approach, and the rapid and extensive scaling of DHIS2, we questioned whether or not there has been a parallel increase in the scaling of improved information use. To date, there has been no rigorous review of the documentation on how exactly DHIS2 data is routinely being used for decision-making and subsequent programming of action. This scoping review addresses this review gap. METHODS: The five-stage approach of Arksey and O'Malley progressed by Levac et al. and Peters was followed. Three databases (PubMed, Web of Science and Embase) were searched, along with relevant conference proceedings and postgraduate theses. In total, over 500 documents were reviewed and data from 19 documents were extracted. RESULTS: Overall, DHIS2 data are being used but there are few detailed descriptions of this usage in peer reviewed or grey literature. We find that, commonly, there exists a centralised versus decentralised pattern of use in terms of access to data and the reporting of data 'up' in the system. We also find that the different conceptualisations of data use and how data use is conceptualised are not made explicit. CONCLUSIONS: We conclude with some suggestions for a way forward, namely: i) the need to document in more detail and share how data are being used, ii) the need to investigate how data were created and who uses such data, iii) the need to design systems based on work practices, and in tandem develop and promote forums in which 'conversations' around data can take place.

Modelo explicativo de não adesão ao paradigma psicossocial da saúde mental / Explanatory model of non-adhesion to the psychosocial mental health paradigm / Modelo explicativo de la no adhesión al paradigma psicosocial de la salud mental

Este estudo teve como objetivo propor um modelo explicativo de não adesão ao paradigma psicossocial da saúde mental a partir dos estereótipos, das crenças sobre a etiologia da doença mental, da percepção de ameaça e do preconceito. Para tanto, contou-se com a participação de 400 universitários, com média de idade de 24,64 anos (DP = 6, 64), sendo a maioria do sexo feminino (75,6%). Para a proposição do modelo, foi realizada uma path analysis. O modelo proposto demonstrou que quanto maior a percepção de ameaça e a concordância com o estereótipo de incapacidade, menor o apoio ao paradigma psicossocial. Ademais, verificou-se que as crenças acerca da etiologia da doença mental e os estereótipos estão na base da percepção de ameaça e todas essas variáveis juntas predizem maior preconceito. Os achados desta pesquisa fornecem subsídios científicos para a realização de intervenções eficazes e consistentes que fortaleçam o paradigma psicossocial no cenário nacional. (AU)

This study aimed to propose an explanatory model of non-adherence to the psychosocial paradigm of mental health based on stereotypes, beliefs about the etiology of mental illness, perception of threat, and prejudice. Participants included a total of 400 university students, with a mean age of 24.64 years (SD = 6, 64), mostly women (75.6%). A path analysis was performed to propose the model, which showed that the greater the perception of threat and the agreement with the disability stereotype, the lower the support for the psychosocial paradigm. Furthermore, it was found that beliefs about the etiology of mental illness and stereotypes are at the basis of the perception of threat and all these variables together predict greater prejudice. The findings of this research provide scientific support for effective and consistent interventions that strengthen the psychosocial paradigm on the national scene. (AU)

Este estudio tuvo como objetivo proponer un modelo explicativo de la no adherencia al paradigma psicosocial de la salud mental basado en estereotipos, creencias sobre la etiología de la enfermedad mental, percepción de amenaza y prejuicio. Para ello participaron 400 estudiantes universitarios, con una edad media de 24,64 años (DS = 6,64), siendo la mayoría mujeres (75,6 %). Para la proposición del modelo, se realizó un path análisis. El modelo sugerido demostró que, a mayor percepción de amenaza y concordancia con el estereotipo de discapacidad, menor apoyo al paradigma psicosocial. Además, se encontró que las creencias sobre la etiología de la enfermedad mental y los estereotipos están en la base de la percepción de amenaza y todas estas variables en conjunto predicen un mayor prejuicio. Los hallazgos de esta investigación brindan soporte científico para ejecutar intervenciones efectivas y consistentes que fortalezcan el paradigma psicosocial en el escenario nacional. (AU)

Optimizing the Health Management Information System in Uttar Pradesh, India: Implementation Insights and Key Learnings.

An effective health management information system (HMIS) that captures accurate, consistent, and relevant data in a timely fashion can enable better planning and monitoring of health programs and improved service delivery, in turn helping increase the impact of different interventions. In 2009, the Government of Uttar Pradesh (GOUP) implemented HMIS, India's national-level health information platform. However, key challenges, including difficulties in accessing the data through a web-based portal and its limited relevance to decision making and managerial needs, reduced its usability at the district and state levels. In 2015, with the support of the Uttar Pradesh Technical Support Unit, the GOUP created its own data platform, the Uttar Pradesh HMIS (UP-HMIS), to capture data elements missing from HMIS but important to UP decision makers. The UP-HMIS was redesigned to capture these data elements to holistically measure and monitor the performance of health programs and inform decision making at the district and state levels. In addition, the GOUP implemented complementary initiatives to improve data quality and data use processes. To improve HMIS data quality, the GOUP established data validation committee meetings at the block, district, and state levels. To promote the use of these validated data, in 2017, the GOUP developed and implemented the UP Health Dashboard, which ranks each of UP's 75 districts on a set of key HMIS priority health indicators. These policy guidelines have brought greater attention to UP-HMIS data quality and use; however, additional strengthening is required to improve the quality and use of HMIS data. There is a need to increase the overall capacity and understanding of HMIS data, not only for staff with specific data-related responsibilities but also for program managers and senior decision makers.

Clinical annotations for prostate cancer research: Defining data elements, creating a reproducible analytical pipeline, and assessing data quality.

BACKGROUND: Routine clinical data from clinical charts are indispensable for retrospective and prospective observational studies and clinical trials. Their reproducibility is often not assessed. We developed a prostate cancer-specific database for clinical annotations and evaluated data reproducibility. METHODS: For men with prostate cancer who had clinical-grade paired tumor-normal sequencing at a comprehensive cancer center, we performed team-based retrospective data collection from the electronic medical record using a defined source hierarchy. We developed an open-source R package for data processing. With blinded repeat annotation by a reference medical oncologist, we assessed data completeness, reproducibility of team-based annotations, and impact of measurement error on bias in survival analyses. RESULTS: Data elements on demographics, diagnosis and staging, disease state at the time of procuring a genomically characterized sample, and clinical outcomes were piloted and then abstracted for 2261 patients (with 2631 samples). Completeness of data elements was generally high. Comparing to the repeat annotation by a medical oncologist blinded to the database (100 patients/samples), reproducibility of annotations was high; T stage, metastasis date, and presence and date of castration resistance had lower reproducibility. Impact of measurement error on estimates for strong prognostic factors was modest. CONCLUSIONS: With a prostate cancer-specific data dictionary and quality control measures, manual clinical annotations by a multidisciplinary team can be scalable and reproducible. The data dictionary and the R package for reproducible data processing are freely available to increase data quality and efficiency in clinical prostate cancer research.

Data Quality of Automated Comorbidity Lists in Patients With Mental Health and Substance Use Disorders.

EHRs provide an opportunity to conduct research on underrepresented oncology populations with mental health and substance use disorders. However, a lack of data quality may introduce unintended bias into EHR data. The objective of this article is describe our analysis of data quality within automated comorbidity lists commonly found in EHRs. Investigators conducted a retrospective chart review of 395 oncology patients from a safety-net integrated healthcare system. Statistical analysis included κ coefficients and a condition logistic regression. Subjects were racially and ethnically diverse and predominantly used Medicaid insurance. Weak κ coefficients ( κ = 0.2-0.39, P < .01) were noted for drug and alcohol use disorders indicating deficiencies in comorbidity documentation within the automated comorbidity list. Further, conditional logistic regression analyses revealed deficiencies in comorbidity documentation in patients with drug use disorders (odds ratio, 11.03; 95% confidence interval, 2.71-44.9; P = .01) and psychoses (odds ratio, 0.04; confidence interval, 0.02-0.10; P < .01). Findings suggest deficiencies in automatic comorbidity lists as compared with a review of provider narrative notes when identifying comorbidities. As healthcare systems increasingly use EHR data in clinical studies and decision making, the quality of healthcare delivery and clinical research may be affected by discrepancies in the documentation of comorbidities.

Accurate and rapid prediction of tuberculosis drug resistance from genome sequence data using traditional machine learning algorithms and CNN.

Effective and timely antibiotic treatment depends on accurate and rapid in silico antimicrobial-resistant (AMR) predictions. Existing statistical rule-based Mycobacterium tuberculosis (MTB) drug resistance prediction methods using bacterial genomic sequencing data often achieve varying results: high accuracy on some antibiotics but relatively low accuracy on others. Traditional machine learning (ML) approaches have been applied to classify drug resistance for MTB and have shown more stable performance. However, there is no study that uses deep learning architecture like Convolutional Neural Network (CNN) on a large and diverse cohort of MTB samples for AMR prediction. We developed 24 binary classifiers of MTB drug resistance status across eight anti-MTB drugs and three different ML algorithms: logistic regression, random forest and 1D CNN using a training dataset of 10,575 MTB isolates collected from 16 countries across six continents, where an extended pan-genome reference was used for detecting genetic features. Our 1D CNN architecture was designed to integrate both sequential and non-sequential features. In terms of F1-scores, 1D CNN models are our best classifiers that are also more accurate and stable than the state-of-the-art rule-based tool Mykrobe predictor (81.1 to 93.8%, 93.7 to 96.2%, 93.1 to 94.8%, 95.9 to 97.2% and 97.1 to 98.2% for ethambutol, rifampicin, pyrazinamide, isoniazid and ofloxacin respectively). We applied filter-based feature selection to find AMR relevant features. All selected variant features are AMR-related ones in CARD database. 78.8% of them are also in the catalogue of MTB mutations that were recently identified as drug resistance-associated ones by WHO. To facilitate ML model development for AMR prediction, we packaged every step into an automated pipeline and shared the source code at https://github.com/KuangXY3/MTB-AMR-classification-CNN .