COVID-19 Limitations on Doodling as a Measure of Burnout

Pre-COVID-19, doodling was identified as a measure of burnout in researchers attending a weekly, in-person health narratives research group manifesting team mindfulness. Under the group’s supportive conditions, variations in doodling served to measure change in participants reported depression and anxiety—internal states directly associated with burnout, adversely affecting healthcare researchers, their employment, and their research. COVID-19 demanded social distancing during the group’s 2020/21 academic meetings. Conducted online, the group’s participants who chose to doodle did so alone during the pandemic. Whether the sequestering of group participants during COVID-19 altered the ability of doodling to act as a measure of depression and anxiety was investigated. Participants considered that doodling during the group’s online meetings increased their enjoyment and attention level—some expressed that it helped them to relax. However, unlike face-to-face meetings during previous non-COVID-19 years, solitary doodling during online meetings was unable to reflect researchers’ depression or anxiety. The COVID-19 limitations that necessitated doodling alone maintained the benefits group members saw in doodling but hampered the ability of doodling to act as a measure of burnout, in contrast to previous in-person doodling. This result is seen to correspond to one aspect of the group’s change in team mindfulness resulting from COVID-19 constraints.

The application of image processing for monitoring student’s attention level during online class

With the COVID-19 pandemic still causing the world to be quarantined in their house to prevent the spread of the virus, this means online classes are still the main method of conducting classes. This project aims to help lecturers monitor the students during class as they are having problems checking whether the students are paying attention or not. This project uses the student’s facial features to determine their attention level using two different coding algorithm Viola-Jones and Sobel edge. These two algorithms help to determine what kind of facial expression that the students are making. The Viola-Jones algorithm detects and captures the student’s facial features such as eyes and mouth while the Sobel edge algorithm detects the edges of the facial features to determine whether the eyes and mouth are open or closed. With the data collected it will run through the database to determine the student’s attention level and inform the lecturer.

Attention and Emotional States during Horticultural Activities of Adults in 20s Using Electroencephalography: A Pilot Study

Since indoor, sedentary lifestyles became prevalent in society, humans have lost a sustainable connection to nature. An intervention utilizing outdoor horticultural activities could address such a challenge, but their beneficial effects on the brain and emotions have not been characterized in a quantitative approach. We aimed to investigate brain activity and emotional changes in adults in their 20s during horticultural activity to confirm feasibility of horticultural activity to improve cognitive and emotional states. Sixty university students participated in 11 outdoor horticultural activities at 2-min intervals. We measured brain waves of participants’ prefrontal cortex using a wireless electroencephalography device while performing horticultural activities. Between activities, we evaluated emotional states of participants using questionnaires. Results showed that each horticultural activity showed promotion of brain activity and emotional changes at varying degrees. The participants during physically intensive horticultural activities—digging, raking, and pruning—showed the highest attention level. For emotional states, the participants showed the highest fatigue, tension, and vigor during digging and raking. Plant-based activities—harvesting and transplanting plants—made participants feel natural and relaxed the most. Therefore, this pilot study confirmed the possibility of horticultural activity as a short-term physical intervention to improve attention levels and emotional stability in adults.

Effects of Breathing Meditation Training on Sustained Attention Level, Mindfulness Attention Awareness Level, and Mental State of Operating Room Nurses

Objectives: In this paper, we explore the effects of breathing meditation training on the sustained attention level, mindfulness attention awareness level, and mental state of nurses in the operating room. Methods: We enrolled 40 nurses from September 2019 to December 2019, and divided them into a control group (N=20) and an observation group (N=20) using a random number table. The control group received routine training, based on which the observation group received breathing meditation training. We compared their sustained attention index, fatigue score, mindfulness attention awareness score, mental state score, work stress score, career satisfaction score, and career happiness index. Results: After training, the sustained attention response time was shorter at 8:00 and 18:00 in the observation group than in the control group (p < .05). The physical fatigue score, mental fatigue score, reduced activity score, reduced motivation score, and overall fatigue score of the observation group were lower than those of the control group (p < .05). The observation group had a higher mindfulness attention awareness score than did the control group (p < .05). The SAS and SDS scores of the observation group were lower than those of the control group (p < .05). The work stress score of the observation group was lower than that of the control group, whereas the career satisfaction score and career happiness index were higher (p < .05). Conclusion: Breathing meditation training can improve the sustained attention level and mindfulness attention awareness level, reduce the feeling of fatigue and work stress, help adjust the mental state, and enhance the career satisfaction and career happiness of nurses in the operating room.

COVID-19 Limitations on Doodling as a Measure of Burnout

Pre-COVID-19, doodling was identified as a measure of burnout in researchers attending a weekly, in-person health narratives research group manifesting team mindfulness. Under the group&rsquo;s supportive conditions, variations in doodling served to measure change in participants&rsquo; reported depression and anxiety&mdash;internal states directly associated with burnout, adversely affecting healthcare researchers, their employment, and their research. COVID-19 demanded social distancing during the group&rsquo;s 2020/21 academic meetings. Conducted online, the group&rsquo;s participants who chose to doodle did so alone during the pandemic. Whether the sequestering of group participants during COVID-19 altered the ability of doodling to act as a measure of depression and anxiety was investigated. Participants considered doodling during the group&rsquo;s online meetings increased their enjoyment and attention level&mdash;some expressed it helped them to relax. However, unlike face-to-face meetings during previous non-COVID-19 years, solitary doodling during online meetings was unable to reflect researchers&rsquo; depression or anxiety. COVID-19 limitations necessitating doodling alone maintained the benefits group members saw in doodling but hampered the ability of doodling to act as a measure of burnout in contrast to previous in-person doodling. This result is seen to correspond to one aspect of the group&rsquo;s change in team mindfulness resulting from COVID-19 constraints.

Exploring Time-Series Forecasting Models for Dynamic Pricing in Digital Signage Advertising

Audience attention is vital in Digital Signage Advertising (DSA), as it has a significant impact on the pricing decision to advertise on those media. Various environmental factors affect the audience attention level toward advertising signage. Fixed-price strategies, which have been applied in DSA for pricing decisions, are generally inefficient at maximizing the potential profit of the service provider, as the environmental factors that could affect the audience attention are changing fast and are generally not considered in the current pricing solutions in a timely manner. Therefore, the time-series forecasting method is a suitable pricing solution for DSA, as it improves the pricing decision by modeling the changes in the environmental factors and audience attention level toward signage for optimal pricing. However, it is difficult to determine an optimal price forecasting model for DSA with the increasing number of available time-series forecasting models in recent years. Based on the 84 research articles reviewed, the data characteristics analysis in terms of linearity, stationarity, volatility, and dataset size is helpful in determining the optimal model for time-series price forecasting. This paper has reviewed the widely used time-series forecasting models and identified the related data characteristics of each model. A framework is proposed to demonstrate the model selection process for dynamic pricing in DSA based on its data characteristics analysis, paving the way for future research of pricing solutions for DSA.

Preferences based interventions to address the use of antibiotics without prescription: a discrete choice experiment

Background: In many countries, concerns have arisen over the population using antibiotics without consulting a physician. This practice can place patients at risk and increase antibiotic resistance in the community. Objective: To evaluate individuals' preferences regarding the use of antibiotics. The study also assessed the likely effectiveness of interventions aimed at reducing inappropriate use of antibiotics. Methods: A discrete choice experiment (DCE) was conducted in Bogotá, Colombia. The attributes were determined by a systematic literature review and four focus group sessions. The DCE included nine factors – cost, time to get attention, level of symptoms, efficacy, safety, among others- and one label -using or not antibiotics. Data analysis was carried out using a generalized multinomial logit (GMNL) model. Marginal probabilities of different sets of attributes' levels were compared to estimate the likely effectiveness of interventions. Results: The survey was administered to 222 participants from diverse socioeconomic backgrounds. The results suggest that participants preferred not taking antibiotics and having a physician as an advisor, but the probability of inappropriate antibiotic use increased as the waiting time or the cost of receiving advice rose. The pharmacy was the preferred source of antibiotics, and participants chose the pharmacy worker (nonprofessional) as an advisor over the nurse on the phone. In the absence of any interventions aimed at reducing the use of antibiotics, approximately 47.3% of people would misuse antibiotics. This reduces to 26.5% when people perceive the efficacy of the antibiotics as low and the potential risks of self-medicating as high. An alternative model using a nursing service would likely lower inappropriate use of antibiotics. Conclusions: Even though people prefer not using antibiotics or visiting a physician in case of disease rather than self-medicating, current access conditions might discourage them from appropriately use antibiotics. The results suggest that interventions that informing people about the risks of self-medication and the low efficacy might significantly reduce inappropriate use of antibiotics. Our results also suggest that programs that empower other health professionals to provide access to antibiotics would likely further lower inappropriate use.