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- Benefits, concerns, and perceptions of knowledge workers regarding a video stress detection softwarePublication . Rodrigues, Matilde; Ferreira, Simão; Figueiredo, Henrique; Rodrigues, Fátima; Moreira, Fernando; Costa, Luís; Rocha, NunoStress is not only highly destructive, causing various mental health disorders (anxiety, insomnia, depression), cardiovascular diseases, poor immune function, and presenteeism, as it is costly. While concerns about occupational stress have increased, new solutions for its management have emerged. Systems based on the use of facial recognition, posture, eye movements, video monitoring, and behavioral stress detection have shown good results. Their drawback has mainly been the recording of the said video feed and privacy threats proceeding. This Focus Groups aimed to raise the opinions, perceptions, and concerns of end users regarding the system under development. With a new solution in mind, we gathered two groups of knowledge workers, one group of team leaders, and a group of consulting psychologists to gather their perceptions. A Focus Groups was conducted online via Microsoft Teams, as COVID-19 restrictions were applied during that period. Against previous reports, knowledge workers showed that privacy threats were not their major concern. Both groups showed that Mental Health was their main focus as the follow-up structure regarding stress detection was the most prevalent topic being close to information sharing and software adaptation. The results highly contribute to the development of future stress detection applications/software and the importance of a detailed and thorough explanation regarding the software framework.
- Exploring the associations between early maladaptive schemas and impulsive and compulsive buying tendenciesPublication . Rocha, Susana ; Fernández, Xosé Manuel ; Castro, Yolanda Rodríguez ; Ferreira, Simão; Teixeira, Liliana; Campos, Carlos; Barbosa Rocha, NunoThe main purpose of this preliminary study was to investigate a potential relationship between early maladaptive schemas (EMSs) and impulsive and compulsive buying tendencies in a sample of young adults (college students). This research adds to the cognitive perspective of consumer behavior that the cognitive schemas putatively associated with early experiences may have a strong impact on impulsive and compulsive buying. Data was obtained from 365 participants in a cross-sectional study design. Participants completed an online survey with the following instruments: Young Schema Questionnaire; Impulsive Buying Tendency Measurement Scale; Richmond Compulsive Buying Scale; and Hospital Anxiety and Depression Scale. Using multiple linear hierarchical regressions, we confirmed that the domain of over vigilance and inhibition schemas was positively associated with impulsive and compulsive buying tendencies, while an opposite association was found for the domain of impaired limits. Being a female was also a predictor of impulsive buying and compulsive buying. The results were discussed in terms of the coping mechanisms to deal with negative emotions, as a way to obtain rewards, or as a way to escape painful self-awareness. Other mechanisms related to the internalization of perfectionist expectations and the propensity to shame were also explored.
- Mad@ work mental health and productivity boosting in the workplacePublication . Rocha, Nuno; Rodrigues, Matilde; Ferreira, SimãoOur work life is changing rapidly. Globalization is ramping up competition, and digitalization is transforming all but the simplest manual labor into knowledge work. These changes don’t come without a price – and it seems that the price is paid in an increase of stress and burnout. The cost of work-related stress in Europe was estimated to be around 200 billion annually and, in the USA, job stress alone is estimated to cost companies approximately 300 billion dollars a year. To face the high costs, the key to success requires tackling the work stress-related issues, first, in an individual level. This project aims to develop novel stress detection solutions for workplaces, which will help to manage and reduce stress in the work context and build safe, positive, and productive work environments. Existing technologies for stress detection have been developed in relatively short-term studies and are not practical and/or mature enough for continuous, real-life usage. To overcome these shortcomings, we will develop novel solutions to detect workplace problems and stress, convenient for long-term real-life use. Pilots in real workplaces will be conducted to achieve project goals and to evaluate developed solutions. Ultimately, our goal is to support and mitigate ongoing transformation, helping individuals flourish and companies thrive, paving the way for healthier workplaces where people throw up their arms, not in frustration or anger but inspiration and excitement.
- The effects of 24-hour sleep deprivation on the human brain: a multimodal neurophysiological approachPublication . Gonçalves, Alice; Pinto, Sara; Ferreira, Simão; Borges, Daniel FilipeIntroduction: Sleep is an important aspect of human health and well-being and influences various physiological and cognitive functions such as learning and attention. On the other hand, sleep deprivation activates the sympathetic nervous system, negatively impacting blood pressure, heart rate, glucose metabolism, cortisol, and hormones. It alters mood, behaviour, and reduces awareness leading to a poor performance, hence the importance of studying the neurophysiological and neurocognitive effects of 24h sleep deprivation. Objective: Our main goal is to investigate the effects of acute sleep deprivation on the cerebral cortex in healthy university students using a multimodal approach and neurocognitive scales. Methods: This study will use a magnetic stimulator to assess neurophysiological changes, while actigraphy will verify sleep deprivation in the intervention group. Neuropsychological assessments include the Trail Making Test (TMT), measuring visual processing speed and cognitive flexibility, the Psychomotor Vigilance Task (PVT), assessing sustained attention through reaction times to unpredictable stimuli and N-Back test measuring working memory by requiring participants to recall objects presented a few steps earlier. EEG data will be recorded using a cap with 32 channels during. This integrated approach provides a comprehensive analysis of the effects of sleep deprivation on cognitive and neurophysiological functions. Expected Results: Hypothetically, there will be a significant decline in cognitive performance, with impairments in key areas such as visual attention, processing speed and cognitive flexibility. These results will likely manifest in longer reaction times, more frequent errors and overall lower task execution.
- Validation of a video-based system to determine heart rate for stress monitoringPublication . Ferreira, Simão; Rodrigues, Matilde; Rocha, NunoStudies estimate that about 50% of all lost workdays are related to occupational stress. Academic researchers have been using heart rate variability (HRV) as an indicator of stress. As a way of providing the needed heart rate data, an unobtrusive approach points to video plethysmography, being a recent method that needs further investigation and validation. Specific barriers such as room lighting conditions and face movement have been identified as the main risks for software progression. The present chapter presents a validation protocol of a video-based system to determine heart rate for stress monitoring, under different illuminance levels and position conditions. We present an in-depth protocol on how to assess the reliability of a video facial recognition software on collecting physiological data (heart rate), and our software results when compared to the gold standard, Electrocardiogram (ECG).
- Advancing the understanding of pupil size variation in occupational safety and health: A systematic review and evaluation of open-source methodologiesPublication . Ferreira, Filipa; Ferreira, Simão; Mateus, Catarina; Rocha, Nuno; Coelho, Luís; Rodrigues, MatildePupil size can be used as an important biomarker for occupational risks. In recent years, there has been an increase in the development of open-source tools dedicated to obtaining and measuring pupil diameter. However, it remains undetermined determined whether these tools are suitable for use in occupational settings. This study explores the significance of pupil size variation as a biomarker for occupational risks and evaluates existing open-source methods for potential use in both research and occupational settings, with the goal of to prevent occupational accidents and improve the health and performance of workers. To this end, a two-phase systematic literature review was conducted in the Web of Science™, ScienceDirect®, and Scopus® databases. For the relevance of monitoring pupil size variation in occupational settings, 15 articles were included. The articles were divided into three groups: mental workload, occupational stress, and mental fatigue. In most cases, pupil dilation increased with workload enhancement and with higher levels of stress. Regarding fatigue, it was noted that an increase in this condition corresponded with a decrease in pupil size. With respect to the open-source methodologies, 16 articles were identified, which were categorized into two groups: algorithms and software. Convolutional neural networks (CNN)1 have exhibited superior performance among the various algorithmic approaches studied. Building on this insight, and considering the evaluations of software options, MEYE emerges as the premier open-source system for deployment in occupational settings due to its compatibility with a standard computer webcam. This feature positions MEYE as a particularly practical tool for workers in stable environments, like those of developers and administrators.
- An unobtrusive multimodal stress detection model & recommender systemPublication . Ferreira, Simão; Correia, Hugo; Rodrigues, Fátima; Rodrigues, Matilde; Rocha, NunoStudies estimate that about 50% of all lost workdays are related to occupational stress. In recent years, several solutions for mental health management, including biofeedback applications, have emerged as a way to enhance employee mental health. Solutions to mitigate risk factors related to the working settings present an enormous potential and a clear contribution. However, most of the work that has been developed is limited to laboratory environments and does not suit real-life needs. Our study proposes an unobtrusive multimodal approach for detecting work-related stress combining videoplethysmography and self-reported measures for stablishing the ground truth in real-life settings. The study involved 28 volunteers over a two-month period. Various physiological signals were collected through a videopletismography solution, while users were performing daily working, for approximately eight hours a day. In parallel, selfreported measures were collected via a pop-up application (developed by the research team) that periodically retrieved the user's perceived stress (amongst other variables) in order to label the physiological data. In order to develop the stress detection model, we pre-processed the data and performed Heart Rate Variability (HRV) feature extraction. Then, we experimented with several machine learning models, utilizing both individual and combined physiological signals to explore all available alternatives. After rigorous evaluation, the best-trained model achieved an accuracy of over 80% and an F1 Score of over 85%. With the stress detection model in place, we are developing a structured intervention model to help reduce stress. This intervention model integrates two interconnected dimensions through digital coaching, which prioritizes personalized recommendations based on user preferences. Our top priority is to ensure user engagement, and we believe that adherence to and adoption of recommended interventions are more likely when users receive recommendations that align with their preferences. Thus, we prioritize personalized recommendations that are tailored to each individual's unique model. After detecting immediate stress peaks and providing real-time feedback on stress levels, our alarm system goes a step further by offering customized recommendations for brief stress relief. The digital coach (intervention model) offers various recommendations and active lifestyle changes such as exercise, task management, weight management, better sleep habits, structured pauses, and other critical interventions. These critical interventions are also based on user preferences, allowing our system to prevent future stress-related incidents and, most importantly, mitigate long-term stress. This project and its methodology demonstrate that truly unobtrusive stress detection is possible and can be performed within the scope of ethical demands. In future work, we will evaluate the responses and beneficial outcomes of implementing a recommender system.
- Challenges of learning human digital twin: case study of mental wellbeing: Using sensor data and machine learning to create HDTPublication . Vildjiounaite, Elena; Kallio, Johanna; Kantorovitch, Julia; Kinnula, Atte; Ferreira, Simão; Rodrigues, Matilde; Rocha, NunoHuman Digital Twin (HDT) is a powerful tool to create a virtual replica of a human, to be used for example for designing interactions with physical systems, preventing cognitive overload, managing human capital, and maintaining a healthy and motivated workforce. Building human twins is a challenging task due to the need to reliably represent each corresponding human being, and the fact that human beings notably differ from each other. Therefore, relying solely on expert knowledge is insufficient, and human twins must learn the specifics of each individual in order to accurately represent them. This paper focuses on AI methods for modelling the mental wellbeing of knowledge workers because the mounting cognitive demands of both white-collar and blue-collar work lead to employees’ stress, and stress leads to diminished creativity and motivation, increased sick leaves, and in severe cases, accidents, burnouts, and disabilities. This paper describes the main building blocks of AI-based detectors of mental stress and highlights the main challenges and future directions of research., which are expected to be relevant also for HDT learning in other domains because the high degree of individuality is ubiquitous in all human activities.
- Uncovering the dynamics of burnout, stress, anxiety, and depression in office workers: an experience sampling approachPublication . Ferreira, Simão; Silva, Inês; Rodrigues, Matilde; Rocha, NunoStress, anxiety, depression, and burnout are recognized as prominent mental health challenges within the workplace, and there is evidence to suggest that several psychosocial risk factors may be associated with the occurrence of these mental health problems. However, few studies have relied on the experience sampling method. To address this lack of knowledge, the present study aimed to characterize these mental health challenges in office workers and identify risk factors associated with their occurrence. The study involved a sample of 31 knowledge workers from a large company. To address the variables of interest, questionnaires were administered to the participants. The results revealed that perceived productivity, level of challenge, level of competence, and level of sleepiness were positively correlated with daily stress levels, whereas psychosocial factors such as workload and time available to perform tasks were found to exacerbate stress. These findings highlight the need to consider these risk factors in prevention and intervention programs aimed at promoting mental health in the workplace. In the future, integrating these factors as predictors of mental health problems in automated detection tools for stress, anxiety, burnout, and depression may prove beneficial.
- The relationship between childhood abuse and adult attachment styles: the mediator role of sensory over-responsivityPublication . Silva, Alexandra; Ferreira, Simão; Pinto, Élia Silva; Rocha, Susana Aguiar; Rocha, Nuno BarbosaChild abuse portrays health and well-being issues that can last for several years, including altering interpersonal behavior. Evidence has shown that these early negative experiences may cause changes in sensory modulation. This study aimed to understand if sensory over-responsivity (SOR) plays an important role in mediating the association between childhood abuse (emotional abuse, emotional neglect, sexual abuse, physical abuse, physical neglect) and attachment-related anxiety or avoidance in adult romantic relationships. An online survey was conducted to examine these associations in a Portuguese community sample (N = 500) aged 18–62 years. The presented mediation models shown a higher mediation percentage for attachment-related anxiety rather than avoidance. All variables predicted the mediator, except sexual abuse which did not predict the overall model when the mediator was included. Our results have implications for individual treatment approaches regarding child abuse victims and can certainly influence intervention strategies.