•A multilevel fusion data framework identifies and removes outliers, filters signal and makes decisions based on multiple applications.•Fusion data optimizes the quality of data and improve the ...decision making.•An accurate and lower cost solution estimates a reference model for the agriculture domain, monitoring few variables, and saving the sensor network resources consumption.
The Internet of Things (IoT) aims to enable objects to sense, identify, and analyze the world, but to achieve such goal cost-effectively, it should involve low-cost solutions. That implies a series of limitations, such as small battery life, limited storage capabilities, low accuracy, and imprecise sensors. Data fusion is one of the most widely used methods for improving sensor accuracy and providing a more precise decision. Therefore, we propose Hydra, a multilevel data fusion architecture, to improve sensor accuracy, identify application target events, and make more accurate decisions. Hydra is composed of three layers: low-level (sensor data fusion), medium-level (events and decision making), and high-level (decision fusion based on multiple applications). In partnership with Embrapa (Brazilian Agricultural Research Corporation), we instantiated Hydra for the smart agriculture domain, and we also developed two applications aiming smart water management. The first application goal was to determine the need for irrigation based on soil moisture levels, and the second ascertained the adequate irrigation time by estimating the crop’s evapotranspiration (rate of water evaporation by the soil and transpiration by plants). We performed a set of experiments to assess Hydra: (i) evaluation of methods to detect and remove outliers; (ii) analyze data resulting from the applications; (iii) the use of machine learning to create a new accurate evapotranspiration model based on the sensors data. The results indicate that a combination of the ESD method (Extreme Studentized Deviate) and WRKF filter (Weighted Outlier-Robust Kalman Filter) was the best method to identify and remove outliers. Moreover, we generated an evapotranspiration model using the SVM (Support Machine Vector) quadratic machine-learning model that produced values close to the evapotranspiration reference model (Penman-Monteith).
The COVID-19 pandemic has challenged the mental health of health care workers, increasing the rates of stress, moral distress (MD), and moral injury (MI). Virtual reality (VR) is a useful tool for ...studying MD and MI because it can effectively elicit psychophysiological responses, is customizable, and permits the controlled study of participants in real time.
This study aims to investigate the feasibility of using an intervention comprising a VR scenario and an educational video to examine MD among health care workers during the COVID-19 pandemic and to use our mobile app for longitudinal monitoring of stress, MD, and MI after the intervention.
We recruited 15 participants for a compound intervention consisting of a VR scenario followed by an educational video and a repetition of the VR scenario. The scenario portrayed a morally challenging situation related to a shortage of life-saving equipment. Physiological signals and scores of the Moral Injury Outcome Scale (MIOS) and Perceived Stress Scale (PSS) were collected. Participants underwent a debriefing session to provide their impressions of the intervention, and content analysis was performed on the sessions. Participants were also instructed to use a mobile app for 8 weeks after the intervention to monitor stress, MD, and mental health symptoms. We conducted Wilcoxon signed rank tests on the PSS and MIOS scores to investigate whether the VR scenario could induce stress and MD. We also evaluated user experience and the sense of presence after the intervention through semi-open-ended feedback and the Igroup Presence Questionnaire, respectively. Qualitative feedback was summarized and categorized to offer an experiential perspective.
All participants completed the intervention. Mean pre- and postintervention scores were respectively 10.4 (SD 9.9) and 13.5 (SD 9.1) for the MIOS and 17.3 (SD 7.5) and 19.1 (SD 8.1) for the PSS. Statistical analyses revealed no significant pre- to postintervention difference in the MIOS and PSS scores (P=.11 and P=.22, respectively), suggesting that the experiment did not acutely induce significant levels of stress or MD. However, content analysis revealed feelings of guilt, shame, and betrayal, which relate to the experience of MD. On the basis of the Igroup Presence Questionnaire results, the VR scenario achieved an above-average degree of overall presence, spatial presence, and involvement, and slightly below-average realism. Of the 15 participants, 8 (53%) did not answer symptom surveys on the mobile app.
Our study demonstrated VR to be a feasible method to simulate morally challenging situations and elicit genuine responses associated with MD with high acceptability and tolerability. Future research could better define the efficacy of VR in examining stress, MD, and MI both acutely and in the longer term. An improved participant strategy for mobile data capture is needed for future studies.
ClinicalTrails.gov NCT05001542; https://clinicaltrials.gov/study/NCT05001542.
RR2-10.2196/32240.
Background:
Oral squamous cell carcinoma (OSCC) is the sixth most common cancer in the world, and the bacterial microbiome has been considered a risk factor that could play an important role in ...carcinogenesis.
Objective:
A bacteriome study was performed by next-generation sequencing in dental plaque, saliva, and tumor samples of 10 OSCC patients and compared with bacteriome in dental plaque and saliva of 10 patients without OSCC.
Methods:
DNA was extracted from all samples and sequenced by Illumina technology MiSeq™. Bioinformatic analyzes were performed for evaluated sequence quality, alpha and beta diversity, bidirectional analysis of variance (p <0.05), and principal component analysis. After establishing bacterial profiles associated with each sample and population, intragroup and intergroup comparisons were carried out. For bacteria identification compatible with eubiosis and dysbiosis processes, a screening was performed based on the frequency of appearance in all patient samples with and without OSCC. Lastly, frequency, average, standard deviation, Chi-square, and Mann Whitney test were calculated.
Results:
Out of the identified 1,231 bacteria in the populations under study, 45 bacterial species were selected, of which 34 were compatible with eubiosis, and 11 were compatible with dysbiosis. Among the bacteria compatible with eubiosis were species of
Lactobacillus
and
Streptococcus
,
Chromobacterium violaceum, Enterobacter asburiae, Mycobacterium chubuense, Mycoplasma penetrans
, and
Brachyspira intermedia
. Among the species associated with dysbiosis,
Providencia stuartii, Capnocytophaga canimorsus, Legionella pneumophila,
and
Mycoplasma hominis
were notable.
Conclusion:
Thirty-four bacterial species may be associated with eubiosis or healthy states and 11 bacterial species could be associated with dysbiosis or pathogenic state, OSCC.
Stress, anxiety, distress, and depression are high among health care workers during the COVID-19 pandemic, and they have reported acting in ways that are contrary to their moral values and ...professional commitments that degrade their integrity. This creates moral distress and injury due to constraints they have encountered, such as limited resources.
The purpose of this study is to develop and show the feasibility of digital platforms (a virtual reality and a mobile platform) to understand the causes and ultimately reduce the moral distress of health care providers during the COVID-19 pandemic.
This will be a prospective, single cohort, pre- and posttest study examining the effect of a brief informative video describing moral distress on perceptual, psychological, and physiological indicators of stress and decision-making during a scenario known to potentially elicit moral distress. To accomplish this, we have developed a virtual reality simulation that will be used before and after the digital intervention for monitoring short-term impacts. The simulation involves an intensive care unit setting during the COVID-19 pandemic, and participants will be placed in morally challenging situations. The participants will be engaged in an educational intervention at the individual, team, and organizational levels. During each test, data will be collected for (1) physiological measures of stress and after each test, data will be collected regarding (2) thoughts, feelings and behaviors during a morally challenging situation, and (3) perceptual estimates of psychological stress. In addition, participants will continue to be monitored for moral distress and other psychological stresses for 8 weeks through our Digital intervention/intelligence Group mobile platform. Finally, a comparison will be conducted using machine learning and biostatistical techniques to analyze the short- and long-term impacts of the virtual reality intervention.
The study was funded in November 2020 and received research ethics board approval in March 2021. The study is ongoing.
This project is a proof-of-concept integration to demonstrate viability over 6 months and guide future studies to develop these state-of-the-art technologies to help frontline health care workers work in complex moral contexts. In addition, the project will develop innovations that can be used for future pandemics and in other contexts prone to producing moral distress and injury. This project aims to demonstrate the feasibility of using digital platforms to understand the continuum of moral distress that can lead to moral injury. Demonstration of feasibility will lead to future studies to examine the efficacy of digital platforms to reduce moral distress.
ClinicalTrials.gov NCT05001542; https://clinicaltrials.gov/ct2/show/NCT05001542.
DERR1-10.2196/32240.
Staffing and resource shortages, especially during the COVID-19 pandemic, have increased stress levels among health care workers. Many health care workers have reported feeling unable to maintain the ...quality of care expected within their profession, which, at times, may lead to moral distress and moral injury. Currently, interventions for moral distress and moral injury are limited.
This study has the following aims: (1) to characterize and reduce stress and moral distress related to decision-making in morally complex situations using a virtual reality (VR) scenario and a didactic intervention; (2) to identify features contributing to mental health outcomes using wearable, physiological, and self-reported questionnaire data; and (3) to create a personal digital phenotype profile that characterizes stress and moral distress at the individual level.
This will be a single cohort, pre- and posttest study of 100 nursing professionals in Ontario, Canada. Participants will undergo a VR simulation that requires them to make morally complex decisions related to patient care, which will be administered before and after an educational video on techniques to mitigate distress. During the VR session, participants will complete questionnaires measuring their distress and moral distress, and physiological data (electrocardiogram, electrodermal activity, plethysmography, and respiration) will be collected to assess their stress response. In a subsequent 12-week follow-up period, participants will complete regular assessments measuring clinical outcomes, including distress, moral distress, anxiety, depression, and loneliness. A wearable device will also be used to collect continuous data for 2 weeks before, throughout, and for 12 weeks after the VR session. A pre-post comparison will be conducted to analyze the effects of the VR intervention, and machine learning will be used to create a personal digital phenotype profile for each participant using the physiological, wearable, and self-reported data. Finally, thematic analysis of post-VR debriefing sessions and exit interviews will examine reoccurring codes and overarching themes expressed across participants' experiences.
The study was funded in 2022 and received research ethics board approval in April 2023. The study is ongoing.
It is expected that the VR scenario will elicit stress and moral distress. Additionally, the didactic intervention is anticipated to improve understanding of and decrease feelings of stress and moral distress. Models of digital phenotypes developed and integrated with wearables could allow for the prediction of risk and the assessment of treatment responses in individuals experiencing moral distress in real-time and naturalistic contexts. This paradigm could also be used in other populations prone to moral distress and injury, such as military and public safety personnel.
ClinicalTrials.gov NCT05923398; https://clinicaltrials.gov/study/NCT05923398.
DERR1-10.2196/54180.
Background
Progress in remote educational strategies was fueled by the advent of the COVID-19 pandemic. This pilot RCT explored the efficacy of a decentralized model of simulation based on principles ...of observational and peer-to-peer learning for the acquisition of surgical skills.
Methods
Sixty medical students from the University of Montreal learned the running subcuticular suture in four different conditions: (1) Control group (2) Self-learning (3) Peer-learning (4) Peer-learning with expert feedback. The control group learned with error-free videos, while the others, through videos illustrating strategic sub-optimal performances to be identified and discussed by students. Performance on a simulator at the end of the learning period, was assessed by an expert using a global rating scale (GRS) and checklist (CL).
Results
Students engaging in peer-to-peer learning strategies outperformed students who learned alone. The presence of an expert, and passive vs active observational learning strategies did not impact performance.
Conclusion
This study supports the efficacy of a remote learning strategy and demonstrates how collaborative discourse optimizes the students’ acquisition of surgical skills. These remote simulation strategies create the potential for implantation in future medical curriculum design.
Trial Registration
: NCT04425499 2020-05-06.
Resumen La declaratoria del estado de emergencia, a causa de la pandemia de la covid-19, exige un análisis de la vigencia de las relaciones contractuales y cómo estas pueden verse afectadas por ...eventos extraordinarios, imprevisibles e irresistibles que impidan el cumplimiento de las prestaciones, así como aquellos casos en los que la alteración de las circunstancias puede llevar a que una de las partes exija al juez recomponga el contenido de la prestación pactada o la resolución del contrato.
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