Reflexões sobre a construção de uma pesquisa qualitativa em psicoterapia on-line / Reflexiones sobre la construcción de una investigación cualitativa en psicoterapia online / Reflections on the construction of a qualitative research in online psychotherapy

RESUMO. Os serviços mediados pela internet oferecem uma diversidade de formas de conexão e interatividade e, em decorrência, surgem novas intervenções em saúde mental, exigindo pesquisas que fundamentem e avaliem tais práticas. Entretanto, os estudos na área são escassos, especialmente diretrizes que auxiliem na condução de pesquisas que envolvam as intervenções baseadas na internet. Nesse sentido, o objetivo deste artigo é indicar orientações para o desenho de pesquisas de intervenção psicológica na internet, tendo como ilustração a construção de uma pesquisa interventiva em psicoterapia on-line, qualitativa, descritiva e longitudinal. São abordados seis aspectos significativos para pesquisas em intervenção digital, incluindo contato com colaboradores, critérios de participação, alcances da pesquisa, monitoramento e avaliação das intervenções, critérios tecnológicos e aspectos éticos no campo digital. São levantados aspectos técnicos, qualitativos e de cuidados necessários para manter a qualidade dos atendimentos e das pesquisas mediadas pelas tecnologias digitais. É urgente à psicologia consolidar um campo de saber que se ocupe tanto das influências das tecnologias nas subjetividades, também, delinear estudos que avaliem com rigor científico o uso da internet para o tratamento e cuidado em saúde mental.

RESUMEN. Los servicios mediados por Internet ofrecen una diversidad de formas de conexión e interactividad y, como resultado, surgen nuevas intervenciones en salud mental, que requieren investigaciones que corroboren y evalúen dichas prácticas. Sin embargo, los estudios en el área son escasos, especialmente las directrices que ayudan a realizar investigaciones que involucran intervenciones basadas en Internet. En este sentido, el objetivo de este artículo es indicar directrices para el diseño de investigación de intervención psicológica en Internet, teniendo como ilustración la construcción de una investigación intervencionista en psicoterapia online, cualitativa, descriptiva y longitudinal. Se abordan seis aspectos significativos para la investigación en intervención digital, incluyendo el contacto con colaboradores, los criterios de participación, el alcance de la investigación, el seguimiento y evaluación de las intervenciones, los criterios tecnológicos y los aspectos éticos en el campo digital. Se plantean aspectos técnicos, cualitativos y asistenciales necesarios para mantener la calidad asistencial y la investigación mediada por las tecnologías digitales. Es urgente que la Psicología consolide un campo de conocimiento que se ocupe tanto de las influencias de las tecnologías en las subjetividades como de esbozar estudios que evalúen con rigor científico el uso de Internet para el tratamiento y cuidado en salud mental.

ABSTRACT Internet-mediated services offer a variety form of connection and interactivity, from this, new mental health interventions emerge, requiring research to validate and evaluate such practices. However, studies in the area are scarce, especially guidelines that assist in conducting research involving Internet-based interventions. The purpose of this study was to indicate guidelines for the design of psychological intervention research mediated by the Internet, based on the construction of an interventional research in online, qualitative, descriptive and longitudinal psychotherapy. Six significant aspects for digital intervention. Six significant aspects for research in digital intervention are addressed, including contact with collaborators, criteria for participation, scope of research, monitoring and evaluation of interventions, technological criteria and ethical aspects in the digital field. Technical, qualitative and care aspects necessary to maintain the quality of care and research mediated by digital technologies are raised. It is urgent for Psychology to consolidate a field of knowledge that deals with the influence of technologies on subjectivities, as well as to design studies that scientifically assess the use of the internet for treatment and care in mental health.

Transforming the provision of healthcare through emerging technology: A strategic transformation.

Why has the health care delivery paradigm and its integral transactions and interactions been left to muddle through, using archaic, 20th century modes and processes of delivery that are overlaid with byz antine medical record databases that pass for "cut ting-edge" technology? What is stalling the digital revolution in the provision of health care services to consumers? Understanding how and why this has happened requires that we briefly explore the evo lution of health care in the United States. Topics discussed include (1): morbidity and mortality: the public health era: (2) Medicare era: the advance of diagnostic and therapeutic technology; (3) the power of the consumer: patient-centered informatics; and (4) planning and execution of strategic transformation of provision of care informatics. Without an informatics focus, our health care system will continue limping along, costing more money and delivering many years of disability. Our most viable solutions revolve around using informatics to measure, guide and become the transformation. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Innovative applications of informatics for families, systems, and health: Introduction to the special issue.

The articles included in this special issue of Families, Systems, & Health on informatics represent distinct elements of health informatics relevant to the implementation and provision of clinical services. Informatics is the collection, analysis, and application of data for direct care decisions in health care and an interdisciplinary field that brings medicine together with computer, cognitive, and social sciences. We frame the contributions of the included articles within the framework of the Quadruple Aim for health care: better outcomes, lower costs, improved patient satisfaction, and improved work life of health care providers. The examples provided aim to show how health informatics provides opportunities to improve care delivered to patients at individual and system levels while both identifying and closing gaps in research addressing the management and use of information generated in the course of delivering health care. The articles in this special issue reflect the cutting edge of health care, research and technology, where there is as much risk as there is promise of delivering stability to our dynamic health care system. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Medicine, Machines, and Medical Education.

While advances in science and technology continue to be at the forefront of the evolution of medical practice, the 21st century is also undergoing a unique and profound cultural shift that is changing the very nature of what it means to be a medical professional, namely humankind's transition to an information-based internet society. Medical care will increasingly depend on computer-generated probabilities guided and supported by a growing variety of individuals in health care-related professions, including statisticians, technologists, and information managers. Perhaps the biggest challenge to the profession will come from the erosion of professional autonomy, driven by smart machines, social networks, and internet search engines. As a result of these and other changes, physicians are facing a systematic loss of control, often without the direct input and leadership of the profession itself. In this commentary, the author urges the profession to adopt several strategies, including shifting its focus from reimbursement to the care patients value most, meaningfully addressing critical issues in health policy, becoming the definitive source for publicly available medical information, reimagining medical education, and overhauling the existing accreditation and licensing systems. Medical education must go beyond a focus on physicians whose professional identity revolves around being the exclusive source of medical knowledge. In the digitized 21st century, medical education should emphasize the centrality of the humanistic interface with patients such that the doctor-patient relationship is paramount in the complex medical world of machines and social media. Removing the roadblocks to successful professional reform is no small task, but the process can begin with a grassroots movement that empowers physicians and facilitates organizational and behavioral change. Failure to take action may well hasten the diminishment of patient care and the profession's trusted role in society.

Impact of a computerized decision support tool deployed in two intensive care units on acute kidney injury progression and guideline compliance: a prospective observational study.

BACKGROUND: Acute kidney injury (AKI) affects a large proportion of the critically ill and is associated with worse patient outcomes. Early identification of AKI can lead to earlier initiation of supportive therapy and better management. In this study, we evaluate the impact of computerized AKI decision support tool integrated with the critical care clinical information system (CCIS) on patient outcomes. Specifically, we hypothesize that integration of AKI guidelines into CCIS will decrease the proportion of patients with Stage 1 AKI deteriorating into higher stages of AKI. METHODS: The study was conducted in two intensive care units (ICUs) at University Hospitals Bristol, UK, in a before (control) and after (intervention) format. The intervention consisted of the AKIN guidelines and AKI care bundle which included guidance for medication usage, AKI advisory and dashboard with AKI score. Clinical data and patient outcomes were collected from all patients admitted to the units. AKI stage was calculated using the Acute Kidney Injury Network (AKIN) guidelines. Maximum AKI stage per admission, change in AKI stage and other metrics were calculated for the cohort. Adherence to eGFR-based enoxaparin dosing guidelines was evaluated as a proxy for clinician awareness of AKI. RESULTS: Each phase of the study lasted a year, and a total of 5044 admissions were included for analysis with equal numbers of patients for the control and intervention stages. The proportion of patients worsening from Stage 1 AKI decreased from 42% (control) to 33.5% (intervention), p = 0.002. The proportion of incorrect enoxaparin doses decreased from 1.72% (control) to 0.6% (intervention), p < 0.001. The prevalence of any AKI decreased from 43.1% (control) to 37.5% (intervention), p < 0.05. CONCLUSIONS: This observational study demonstrated a significant reduction in AKI progression from Stage 1 and a reduction in overall development of AKI. In addition, a reduction in incorrect enoxaparin dosing was also observed, indicating increased clinical awareness. This study demonstrates that AKI guidelines coupled with a newly designed AKI care bundle integrated into CCIS can impact patient outcomes positively.

Jacson Barros (Datasus) apresenta o Programa Conecte SUS

Jacson Barros, diretor do Departamento de Informática do SUS (Datasus), participou hoje (14) do segundo dia da Câmara Técnica de Informação e Informática do Conass, onde apresentou o Conecte SUS aos técnicos das secretarias estaduais de saúde presentes na reunião.

Extensions and adaptations of existing medical information system in order to reduce social contacts during COVID-19 pandemic.

OBJECTIVE: The main objective of this paper is the reduction of the COVID-19 pandemic spread by increasing the degree of social distancing by using and upgrading the existing Medical Information System (MIS). MATERIAL AND METHODS: The existing MIS MEDIS.NET, currently used in the largest health center in the Balkans, has been adapted and further developed. RESULTS: During the adaptation of existing MIS MEDIS.NET 4 new and 9 existing modules were developed. A quick questionnaire for the smart triage of patients was also implemented. DISCUSSION: The adapted MIS successfully influenced the reduction of social contacts within the Health Center Nis. The need for the arrival of children and their parents to receive appropriate health certificates for the school enrolment is reduced. The therapy of chronic patients has been prolonged for 6 months via an electronic prescription. An online service for the communication between patients and the chosen physicians is provided. Possible social contacts and exposure to the viral environment of patients are reduced by making appointments in extended slots and at determined physical locations. Patients are notified per SMS or email about the availability of chosen and physician on duty. The social distancing of patients and physicians is also established by sending laboratory analyses per email or SMS. Keeping the central registry for COVID-19 is enabled throughout the country. CONCLUSION: The smart adaptation of MIS, and its collaboration with other state systems can significantly influence the reduction of social contacts and thus mitigate the consequences of COVID-19 pandemic.

Assessment of the many faces of PsA: single and composite measures in PsA clinical trials.

PsA is a complex, heterogeneous disease that can place a large burden on patients' psychological and physical well-being. The multifaceted nature of PsA poses a significant assessment challenge, both in randomized control trials and in clinical practice. In recent years, there has been much progress in the development of unidimensional and composite measures of disease activity, as well as of questionnaires that capture the patient's perspective of the condition. Despite these advances, there remains uncertainty around which tools to implement within a research setting. This review aims to summarize the currently available clinical and patient-derived assessment tools, providing a practical and informative resource for the assessment of PsA. This review will also explore recent advancements in digital approaches to the assessment of rheumatological conditions. This will highlight the potential for digitalization in the assessment and monitoring of PsA, outlining innovative means of capturing disease activity and treatment response.

[Microdatasus: a package for downloading and preprocessing microdata from Brazilian Health Informatics Department (DATASUS)]. / Microdatasus: pacote para download e pré-processamento de microdados do Departamento de Informática do SUS (DATASUS).

This study aimed to develop an algorithm for downloading and preprocessing microdata furnished by the Brazilian Health Informatics Department (DATASUS) for various health information systems, using the R statistical programming language. The package allows downloading and preprocessing data from various health information systems, with the inclusion of labeling categorical fields in the files. The download function was capable of directly accessing and reducing the workload for the selection of microdata files and variables in DATASUS, while the preprocessing function enabled automatic coding of various categorical fields. The package thus enables a continuous workflow in the same program, in which the algorithm allows downloading and preprocessing and other packages in R allow analyzing data from the health information systems in the Brazilian Unified National Health System (SUS).

O objetivo do estudo foi desenvolver um algoritmo capaz de realizar o download e o pré-processamento de microdados fornecidos pelo Departamento de Informática do SUS (DATASUS) para diversos sistemas de informações em saúde para a linguagem de programação estatística R. O pacote desenvolvido permite o download e o pré-processamento de dados de diversos sistemas de informação em saúde, com a inclusão da rotulagem dos campos categóricos nos arquivos. A função de download foi capaz de acessar diretamente e reduzir o volume de trabalho para a seleção de arquivos e variáveis de microdados junto ao DATASUS. Já a função de pré-processamento foi capaz de efetuar a codificação automática de diversos campos categóricos. Dessa forma, a utilização desse pacote possibilita um fluxo de trabalho contínuo no mesmo programa, no qual esse algoritmo permite o download e o pré-processamento, e outros pacotes do R permitem a análise de dados dos sistemas de informação em saúde do Sistema Único de Saúde (SUS).

El objetivo del estudio fue desarrollar un algoritmo capaz de realizar la descarga y pre-procesamiento de microdatos, proporcionados por el Departamento de Informática del SUS (DATASUS), para diversos sistemas de información en salud, así como para el lenguaje de programación estadístico R. El paquete desarrollado permite la descarga y preprocesamiento de datos de diversos sistemas de información en salud, con la inclusión del rótulo de los campos categóricos en los archivos. La función de descarga se mostró capaz de acceder directamente y reducir el volumen de trabajo para la selección de archivos y variables de microdatos a través del DATASUS, mientras que la función de pre-procesamiento fue capaz de efectuar la codificación automática de diversos campos categóricos. De esta forma, la utilización de este paquete posibilita un flujo de trabajo continuo en el mismo programa, donde este algoritmo permite la descarga y preprocesamiento y otros paquetes del R permiten el análisis de datos de los sistemas de información en salud del Sistema Único de Salud (SUS).

Verifiable fully outsourced attribute-based signcryption system for IoT eHealth big data in cloud computing.

The entrance of Internet of Things (IoT) technologies to healthcare industry has impacted the explosion of eHealth big data. Cloud computing is widely considered to be the promising solution to store this data because of the presence of abundant resources at a lower cost. However, the privacy and security of the IoT generated data cannot be ensured as the data is kept far from the owner's phys- ical domain. In order to resolve the underlined issues, a reassuring solution is to adopt attribute-based signcryption (ABSC) due to the desirable cryptographic properties it holds including fine-grained ac- cess control, authentication, confidentiality and data owner privacy. Nonetheless, executing expensive computation such as pairing and modular exponential operations in resource-constrained IoT device platform can be too taxing and demanding. To address the challenges stated above, we proposed in this paper, a more efficient scheme where computation power is borrowed from the cloud server to process expensive computations while leaving simple operations to local users. In order to realize this, trusted attribute authority, signcryptor and designcryptor outsources to the cloud expensive tasks for key gener- ation, signcryption and designcryption respectively. Moreover, validity and correctness of outsourced computations can be verified by employing outsourcing verification server. Security analysis, compar- isons evaluation and simulation of the proposed scheme is presented. The output demonstrates that it is efficient, secure and therefore suitable for application in resource-constrained IoT devices.

Algebraic secret sharing using privacy homomorphisms for IoT-based healthcare systems.

Healthcare industry is one of the promising fields adopting the Internet of Things (IoT) solutions. In this paper, we study secret sharing mechanisms towards resolving privacy and security issues in IoT-based healthcare applications. In particular, we show how multiple sources are possible to share their data amongst a group of participants without revealing their own data to one another as well as the dealer. Only an authorised subset of participants is able to reconstruct the data. A collusion of fewer participants has no better chance of guessing the private data than a non-participant who has no shares at all. To realise this system, we introduce a novel research upon secret sharing in the encrypted domain. In modern healthcare industry, a patient's health Article often contains data acquired from various sensor nodes. In order to protect information privacy, the data from sensor nodes is encrypted at once and shared among a number of cloud servers of medical institutions via a gateway device. The complete health Article will be retrieved for diagnosis only if the number of presented shares meets the access policy. The retrieval procedure does not involve decryption and therefore the scheme is favourable in some time-sensitive circumstances such as a surgical emergency. We analyse the pros and cons of several possible solutions and develop practical secret sharing schemes for IoT- based healthcare systems.

Medical assertion classification in Chinese EMRs using attention enhanced neural network.

Electronic medical records (EMRs), such as hospital discharge summaries, contain a wealth of information only expressed in natural language. Automated methods for extracting information from these records must be able to recognize medical concepts in text and their semantic context. A contextual property critical to reason on information from EMRs is the doctor's belief status or assertion of the patient's medical problem. Research on the medical assertion classification (MAC) can establish the foundation for various health data analyses and clinical applications. However, previous MAC studies are mainly based on traditional machine learning methods which mostly require manually constructed features and the original unlabeled data cannot be easily and effectively applied to classification or classification tasks. Furthermore, external medical knowledge such as various medical dictionary bases, which provides rich explain and definition information about medical entity, is rarely utilized in existing neural network models of medical information extraction. In this study, we propose a deep neural network architecture enhanced by medical knowledge attention layer through combining GRU neural network with CNN model to classify the assertion type of medical problem such as disease and symptom in Chinese EMRs. The attention layer in the model is applied to integrate entity representations learned from medical dictionary bases as query for encoding. Experimental results on own manually annotated corpus indicate our approach achieves better performance compared to existing methods.

Robust authentication for paper-based text documents based on text watermarking technology.

Aiming at the problem of easy tampering and difficult integrity authentication of paper text documents, this paper proposes a robust content authentication method for printed documents based on text watermarking scheme resisting print-and-scan attack. Firstly, an authentication watermark signal sequence related to content of text document is generated based on the Logistic chaotic map model; then, the authentication watermark signal sequence is embedded into printed paper document by using a robust text watermarking scheme; finally, the watermark information is extracted from scanned image of paper document, and compared with the authentication watermark information calculated in real time by the text document content obtained by OCR technology, thereby performing content integrity authentication of the paper text documents. Experimental results show that our method can achieve the robust content integrity authentication of paper text documents, and can also accurately locate the tampering position. In addition, the document after embedding the watermark information has a good visual effect, and the text watermarking scheme has a large information capacity.

Rural and Urban Differences in the Adoption of New Health Information and Medical Technologies.

BACKGROUND: This statewide survey sought to understand the adoption level of new health information and medical technologies, and whether these patterns differed between urban and rural populations. METHODS: A random sample of 7,979 people aged 18-75 years, stratified by rural status and race, who lived in 1 of 34 Indiana counties with high cancer mortality rates and were seen at least once in the past year in a statewide health system were surveyed. RESULTS: Completed surveys were returned by 970 participants. Rural patients were less likely than urban to use electronic health record messaging systems (28.3% vs 34.5%, P = .045) or any communication technology (43.0% vs 50.8%, P = .017). Rural patients were less likely to look for personal health information for someone else's medical record (11.0% vs 16.3%, P = .022), look-up test results (29.5% vs 38.3%, P = .005), or use any form of electronic medical record (EMR) access (57.5% vs 67.1%, P = .003). Rural differences in any use of communication technology or EMRs were no longer significant in adjusted models, while education and income were significantly associated. There was a trend in the higher use of low-dose computed tomography (CT) scan among rural patients (19.1% vs 14.4%, P = .057). No significant difference was present between rural and urban patients in the use of the human papilloma virus test (27.1% vs 26.6%, P = .880). CONCLUSIONS: Differences in health information technology use between rural and urban populations may be moderated by social determinants. Lower adoption of new health information technologies (HITs) than medical technologies among rural, compared to urban, individuals may be due to lower levels of evidence supporting HITs.

Innovation in surgery/operating room driven by Internet of Things on medical devices.

BACKGROUND: With the improvement of sensor technology, the trend of Internet of Things (IoT) is affecting the medical devices. The aim of this study is to verify whether it is possible to "visualize instrument usage in specific procedures" by automatically accumulating the digital data related to the behavior of surgical instruments/forceps in laparoscopic surgery. METHODS: Five board-certified surgeons (PGY 9-24 years) performed laparoscopic cholecystectomy on 35-kg porcine (n = 5). Radio frequency identifier (RFID) was attached to each forceps with RFID readers installed on the left/right of the operating table. We automatically recorded the behavior by tracking the operator's right/left hands' forceps with RFID. The output sensor was installed in the electrocautery circuit for automatic recordings of the ON/OFF times and the activation time. All data were collected in dedicated software and used for analysis. RESULTS: In all cases, the behaviors of forceps and electrocautery were successfully recorded. The median operation time was 1828 s (range 1159-2962 s), of which the electrocautery probe was the longest held on the right hand (1179 s, 75%), followed by Maryland dissectors (149 s, 10%), then clip appliers (91 s, 2%). In contrast, grasping forceps were mainly used in the left hand (1780 s, 93%). The activation time of electrocautery was only 8% of the total use and the remaining was mainly used for dissection. These situations were seen in common by all operators, but as a mentor surgeon, there was a tendency to change the right hand's instruments more frequently. The median activation time of electrocautery was 0.41 s, and these were confirmed to be 0.14-0.57 s among the operators. CONCLUSION: By utilization of IoT for surgery, surgical procedure could be "visualized." This will improve the safety on surgery such as optimal usage of surgical devices, proper use of electrocautery, and standardization of the surgical procedures.

Term-Based Personalization for Feature Selection in Clinical Handover Form Auto-Filling.

Feature learning and selection have been widely applied in many research areas because of their good performance and lower complexity. Traditional methods usually treat all terms with same feature sets, such that performance can be damaged when noisy information is brought via wrong features for a given term. In this paper, we propose a term-based personalization approach to finding the best features for each term. First, features are given as the input so that we focus on selection strategies. Second, the importance of each feature subset to a given term is evaluated by the term-feature probabilistic relevance model. We present a feature searching method to generate feature candidate subsets for each term, since evaluating all the possible feature subsets is computationally intensive. Finally, we obtain the personalized feature set for each term as a subset of all features. Experiments have been conducted on the NICTA Synthetic Nursing Handover dataset and the results show that our approach is promising and effective.

Identify and monitor clinical variation using machine intelligence: a pilot in colorectal surgery.

Standardized clinical pathways are useful tool to reduce variation in clinical management and may improve quality of care. However the evidence supporting a specific clinical pathway for a patient or patient population is often imperfect limiting adoption and efficacy of clinical pathway. Machine intelligence can potentially identify clinical variation and may provide useful insights to create and optimize clinical pathways. In this quality improvement project we analyzed the inpatient care of 1786 patients undergoing colorectal surgery from 2015 to 2016 across multiple Ohio hospitals in the Cleveland Clinic System. Data from four information subsystems was loaded in the Clinical Variation Management (CVM) application (Ayasdi, Inc., Menlo Park, CA). The CVM application uses machine intelligence and topological data analysis methods to identify groups of similar patients based on the treatment received. We defined "favorable performance" as groups with lower direct variable cost, lower length of stay, and lower 30-day readmissions. The software auto-generated 9 distinct groups of patients based on similarity analysis. Overall, favorable performance was seen with ketorolac use, lower intra-operative fluid use (< 2000 cc) and surgery for cancer. Multiple sub-groups were easily created and analyzed. Adherence reporting tools were easy to use enabling almost real time monitoring. Machine intelligence provided useful insights to create and monitor care pathways with several advantages over traditional analytic approaches including: (1) analysis across disparate data sets, (2) unsupervised discovery, (3) speed and auto-generation of clinical pathways, (4) ease of use by team members, and (5) adherence reporting.