Mental Fatigue Research Articles

Investigating the Comparative Effectiveness of Yoga and Relaxation Therapy on Restlessness, Fatigue and Difficulty Concentrating in Multiple Sclerosis Patients

Background: Multiple sclerosis (MS) is a long-term autoimmune disorder affecting the central nervous system, leading to reduced quality of life and impaired physical and psychological functions. Objectives: This study aims to examine the relative efficacy of yoga and relaxation therapy in improving sleep disturbances, fatigue, and cognitive impairment among individuals diagnosed with MS. Methods: This study employed a semi-experimental research design, including a pre-test, post-test, and follow-up over three months. The target population comprised all MS patients referred to the Iranian MS Association in Tehran between July and November 2023. Sixty participants were selected using purposive sampling and randomly assigned to research groups: Two yoga therapy groups with 17 participants each, a relaxation therapy group with 16 participants, and a control group with 18 participants. The yoga therapy group participated in twelve 90-minute sessions twice a week, while the control group received no intervention and was placed on a waiting list. Various tools, including the Multidimensional Fatigue Inventory (MFI), Cohen-Mansfield Agitation Inventory (CMAI-O), and a concentration skills questionnaire, were used to collect data. The data were analyzed using ANOVA, Bonferroni post hoc test, MANCOVA, and Kruskal-Wallis H tests with a significance level of 0.05, utilizing SPSS 27 software. Results: The study found a significant difference (P < 0.001) in the restlessness factor in both the post-test and follow-up phases. Additionally, there was a significant difference (P < 0.001) in the levels of physical fatigue, mental fatigue, decreased activity, and decreased motivation in both the post-test and follow-up phases, indicating significant changes in the fatigue factor among the research groups. However, there was no significant difference in the general fatigue component between the research groups. A significant difference (P < 0.001) was also found in the concentration factor, particularly in the components of voluntary and involuntary concentration, during both the post-test and follow-up stages. Conclusions: The results of this study indicate that both yoga and relaxation therapy techniques significantly reduce restlessness, physical tiredness, mental fatigue, decreased activity, and decreased motivation. Furthermore, the findings validate that both yoga and relaxation therapy techniques effectively enhance voluntary and involuntary concentration.

Human Operator Mental Fatigue Assessment Based on Video: ML-Driven Approach and Its Application to HFAVD Dataset

The detection of the human mental fatigue state holds immense significance due to its direct impact on work efficiency, specifically in system operation control. Numerous approaches have been proposed to address the challenge of fatigue detection, aiming to identify signs of fatigue and alert the individual. This paper introduces an approach to human mental fatigue assessment based on the application of machine learning techniques to the video of a working operator. For validation purposes, the approach was applied to a dataset, “Human Fatigue Assessment Based on Video Data” (HFAVD) integrating video data with features computed by using our computer vision deep learning models. The incorporated features encompass head movements represented by Euler angles (roll, pitch, and yaw), vital signs (blood pressure, heart rate, oxygen saturation, and respiratory rate), and eye and mouth states (blinking and yawning). The integration of these features eliminates the need for the manual calculation or detection of these parameters, and it obviates the requirement for sensors and external devices, which are commonly employed in existing datasets. The main objective of our work is to advance research in fatigue detection, particularly in work and academic settings. For this reason, we conducted a series of experiments by utilizing machine learning techniques to analyze the dataset and assess the fatigue state based on the features predicted by our models. The results reveal that the random forest technique consistently achieved the highest accuracy and F1-score across all experiments, predominantly exceeding 90%. These findings suggest that random forest is a highly promising technique for this task and prove the strong connection and association among the predicted features used to annotate the videos and the state of fatigue.

Driving Fatigue Onset and Visual Attention: An Electroencephalography-Driven Analysis of Ocular Behavior in a Driving Simulation Task

Attentional deficits have tragic consequences on road safety. These deficits are not solely caused by distraction, since they can also arise from other mental impairments such as, most frequently, mental fatigue. Fatigue is among the most prevalent impairing conditions while driving, degrading drivers’ cognitive and physical abilities. This issue is particularly relevant for professional drivers, who spend most of their time behind the wheel. While scientific literature already documented the behavioral effects of driving fatigue, most studies have focused on drivers under sleep deprivation or anyhow at severe fatigue degrees, since it is difficult to recognize the onset of fatigue. The present study employed an EEG-driven approach to detect early signs of fatigue in professional drivers during a simulated task, with the aim of studying visual attention as fatigue begins to set in. Short-range and long-range professional drivers were recruited to take part in a 45-min-long simulated driving experiment. Questionnaires were used to validate the experimental protocol. A previously validated EEG index, the MDrow, was adopted as the benchmark measure for identifying the “fatigued” spans. Results of the eye-tracking analysis showed that, when fatigued, professional drivers tended to focus on non-informative portions of the driving environment. This paper presents evidence that an EEG-driven approach can be used to detect the onset of fatigue while driving and to study the related visual attention patterns. It was found that the onset of fatigue did not differentially impact drivers depending on their professional activity (short- vs. long-range delivery).

Brain Abscess Causes Brain Damage With Long-Lasting Focal Cerebral Hypoactivity that Correlates With Abscess Size: A Cross-Sectional 18F-Fluoro-Deoxyglucose Positron Emission Tomography Study.

Bacterial brain abscesses may have long-term clinical consequences, eg, mental fatigue or epilepsy, but long-term structural consequences to the brain remain underexplored. We asked if brain abscesses damage brain activity long term, if the extent of such damage depends on the size of the abscess, and if the abscess capsule, which is often left in place during neurosurgery, remains a site of inflammation, which could explain long-lasting symptoms in patients with brain abscess. 2-[18F]-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (FDG-PET/CT), electroencephalography, and MRI were performed 2 days to 9 years after neurosurgery for bacterial brain abscess. FDG-PET/CT revealed hypometabolism in the neocortex or cerebellum overlying the previous bacterial abscess in 38 of 40 patients. The larger the abscess, the greater was the extent of the subsequent hypometabolism (r = 0.63; p = 3 × 10-5). In 9 patients, the extent of subsequent hypometabolism seemed to coincide with the extent of peri-abscess edema in the acute phase. Follow-up MRI after ≥1 year in 9 patients showed focal tissue loss and gliosis. In 13 patients with abnormal electroencephalography recordings, abnormalities extended beyond the cerebral lobe affected by the abscess, indicating damage to wider brain networks. The abscess capsule had an FDG signal indicating inflammation only during the first week after neurosurgical pus drainage. The bigger a brain abscess is allowed to grow, the more extensive is the long-term focal reduction in brain activity. This finding emphasizes the need for rapid neurosurgical intervention. The abscess capsule does not display long-lasting inflammation and probably does not explain long-term symptoms after brain abscess.

Effects of School-led Greenspace Interventions on Mental, Physical and Social Wellbeing in Children and Adolescents: A Systematic Review

AbstractPromoting children’s and adolescents’ mental, physical, and social wellbeing is highly important to help them learn, create social connections, and stay healthy. Nature has the potential to restore cognition, reduce stress and mental fatigue, and improve wellbeing, all factors that are conducive to learning. There is growing interest in understanding the effects of nature on the wellbeing of children and adolescents, particularly in the school context. This paper presents a PRISMA-guided systematic review of the literature examining the effects of school-led nature interventions on the mental, physical, and social wellbeing of school children and adolescents aged 5 to 19 years. Examples of school-led nature interventions include outdoor learning, walks in nature and green schoolyards. Experimental and quasi-experimental studies employing quantitative measures were selected, yielding 19 studies from 17 papers. Included studies were rated as being of high (n = 6) and moderate quality (n = 13). The results provide some evidence that nature exposure in the school context can improve the wellbeing of children and adolescents, particularly their positive affect, physical activity, and social relationships/interactions. The wellbeing effects of school-led nature interventions were also examined according to age and gender, with results indicating a gender effect, but inconclusive findings for age. Findings from this review support the integration of nature in schools to enhance the mental, physical and social wellbeing of children and adolescents.

Prolonged exertion of self-control causes increased sleep-like frontal brain activity and changes in aggressivity and punishment

Impulsive reactions in social interactions may result in poor or even detrimental outcomes. Particular cognitive states, such as mental fatigue induced by extended practice with cognitively demanding activities, especially if combined with sleep restriction or deprivation, seem to impair the individuals' ability to exert self-control effectively and may result in impulsive behaviors, including aggressive acts. We demonstrate that exertion of self-control for as little as 45 min can lead to an increased propensity for engaging in aggressive acts in the context of socially relevant choices, as measured by a set of economic games. Also, we show that such behavioral changes are associated with increased sleep-like (delta) activity within frontal brain areas related to decision-making and impulse control. The local occurrence of sleep-like slow waves may lead to a disengagement of frontal areas and explain the reduced ability of individuals to exert self-control effectively. Our results suggest that sleep-like activity may emerge within the awake brain within a relatively short time scale, with detectable effects on socially relevant behavior.

Viable strategies for enhancing performance in ball sports by mitigating mental fatigue: A systematic review.

Ball sports demand precise control of body and ball while executing tactics and team coordination, which leads to cognitive depletion and mental fatigue. The detrimental effects of mental fatigue on physical, technical, cognitive, and tactical performance in ball sports are evident, highlighting the need for effective management of mental fatigue as a crucial component of modern sports science. This review aims to systematically study and integrate existing experiments on mental fatigue recovery interventions to identify viable strategies for mitigating its impacts. Following PRISMA guidelines, electronic databases including Web of Science, PubMed, SPORTDiscus, and Scopus were used for literature screening. Studies that induced mental fatigue followed by interventions aimed at mental fatigue recovery were included in this review, resulting in 6 articles primarily focused on basketball, soccer, and golf. Short-term interventions such as music listening, mindfulness training, self-talk, and natural visual stimuli have been shown as effective strategies to alleviate mental fatigue and enhance technical and cognitive performance in ball sports. However, their practical application in real-game environments requires further research and validation. Additionally, future research should explore defensive skills and tactical performance as viable directions for study.

An Incongruent 2-Minute Stroop Task Alters the Response Time Performance in Semi-Elite Soccer Players: A Pilot Study

Introduction: Mental fatigue is a key factor in soccer that can affect physical performance. Mental fatigue protocols based on the Stroop test used in soccer involve extensive time, ranging from 10 to 30 min. Offering a protocol with a shorter duration that is more applicable in ecological situations seems to be an exciting challenge. Objective: To analyze the effects of a mental fatigue induction protocol (2 min Stroop test in its incongruent mode) on decision-making, response time, and technical execution accuracy in soccer players. Methods: A total of 18 semi-elite soccer male players, 25.83 (4.71) years from a Spanish soccer team, participated in this cross-sectional study. The 2 min incongruent Stroop test was used like mental fatigue protocol, followed by a specific analytical soccer task. The Wilcoxon signed-rank and Chi-squared tests were used to analyze the statistical differences. Results: A significant increase in participants’ response time after the fatigue protocol (p < 0.001; r = 0.878) was observed. Regarding the variables of correct decision (p = 0.457; r = 0.031) and technical execution accuracy (p = 1; r < 0.001), no significant differences were found. Additionally, no differences were observed between the first and second attempts of the 2 min incongruent Stroop test, in terms of execution accuracy, errors, or total words. Conclusions: The 2 min Stroop incongruent task may induce some degree of mental fatigue, leading to slower response time during certain technical tasks in semi-elite soccer players. However, this Stroop task was insufficient to promote significant changes in the accuracy of technical execution and the effectiveness of decision-making.

Healthcare workers' views on antibiotic prescribing and stewardship during the COVID-19 pandemic at an NHS Foundation Trust in England: a cross-sectional survey

Abstract Introduction Antimicrobial resistance (AMR) is a rapidly escalating global health challenge, projected to cause 10 million deaths annually by 2050.1 In response, the UK Government developed a five-year national action plan, 'Confronting Antimicrobial Resistance 2024 to 2029,' aimed at optimising antimicrobial use and implementing antimicrobial stewardship.2 The COVID-19 pandemic has significantly impacted the healthcare system, jeopardising public health and causing millions of deaths worldwide. The pandemic has exacerbated AMR due to increased antimicrobial therapy and misuse.3 Aim This study explores healthcare workers’ (HCWs) views towards antibiotic prescribing, AMS and AMR during the COVID-19 pandemic in a UK secondary care setting. Methods This cross-sectional study employed an online questionnaire survey conducted at an NHS Foundation Trust in the East of England, targeting doctors, nurses, and pharmacists. The total eligible participants comprised 5,636 doctors, 2,140 nurses, and 206 pharmacists. Data collection was carried out using Qualtrics XM from 12 June to 13 September 2023. Inclusion criteria required healthcare workers (HCWs) to be adults aged 25 or older, registered with relevant professional bodies, and employed during the pandemic. Data analysis involved both descriptive statistics and qualitative methods to interpret participants’ open-ended responses to the question, “What lessons have been learnt during the COVID-19 pandemic?” This study was registered under ISRCTN number 14825813 and received ethical approval from the University of Hertfordshire Ethics and Health Research Authority (HRA) (REC reference number 22/EM/0161). The Citizens Senate reviewed the study protocol to ensure public and patient involvement. Results A total of 23 HCWs completed the survey, including 12 pharmacists, nine doctors, and two nurses. The survey included an open-text section where respondents shared lessons learned during the COVID-19 pandemic. Among pharmacists, 75% (9 out of 12) identified inappropriate antibiotic use without clinical justification as a significant issue, and 67% (8 out of 12) reported an increase in healthcare-associated infections (HCAIs). Additionally, 83% (10 out of 12) noted the positive impact of technology platforms and antibiotic reviews on implementing effective and sustainable AMS. Among doctors, 89% (8 out of 9) emphasised the need for reliable information dissemination, observing that social media often overshadowed evidence-based guidelines. Additionally, 78% (7 out of 9) stressed the importance of staying informed about resistance patterns and antibiotic prescribing trends. All nurses highlighted the significance of AMR awareness and reported that mental fatigue affected decision-making during the pandemic. Discussion/Conclusion This study highlights the essential role of technology platforms in enhancing antimicrobial stewardship practices and the necessity of disseminating reliable information to counter misinformation. The pandemic highlighted the need for clear guidelines and robust communication strategies to support clinical practices. However, this study has limitations, including a small sample size of 23 participants, which may affect the generalisability of the findings. Future research should include larger, more diverse samples to validate these findings and assess specific AMS interventions. The study also revealed the importance of resilient AMS implementation to optimise antibiotic use and improve patient outcomes. Achieving this requires ongoing AMS education, interdisciplinary collaboration, and adaptive strategies to effectively mitigate antimicrobial resistance.

Associations between major depressive disorder and performance-based and self-reported music cognition

BackgroundThere is evidence that major depressive disorder (MDD) comes with multiple cognitive impairments including deficits in perception and memory. Music cognition is one of the least explored cognitive functions in relation to MDD, with some studies pointing to mild amusic deficits. These findings, however, are derived only from performance-based tests. Our objectives were to explore differences in music perception and memory between individuals with MDD and a control group, in both performance test and self-report of amusic dysfunction, and to assess the correlation between these measures.MethodWe recruited 62 participants, including MDD individuals (n = 34) diagnosed with the Mini International Neuropsychiatric Interview and controls (n = 18). All the participants were evaluated with the Montreal Battery for Evaluation of Amusia (MBEA) and the Amusic Dysfunction Inventory (ADI).ResultsNone of the assessed dimensions from the MBEA or the ADI showed statistical differences between groups. Some significant associations were found between ADI's Vocal Production and the MBEA's three tests of the melodic dimension (Scale, Contour and Interval) and between MBEA's Scale and Memory, Meter and ADI's Melodic Perception, and tests of Memory from each respective instrument.ConclusionResults suggest that perception and memory of basic music stimuli are not among the cognitive deficits within MDD, however, they may be indirectly affected by other cognitive phenomena common to this psychopathology, such as poor sustained concentration due to mental fatigue.

Safety and Efficacy of Ashwagandha Root Extract on Cognition, Energy and Mood Problems in Adults: Prospective, Randomized, Placebo-Controlled Study.

This prospective, randomized, placebo-controlled study assessed the effects of Ashwagandha root extract (ARE) on cognition, energy, and mood in adults with self-reported cognitive and energy problems. Healthy subjects aged 30-75 years were randomized to receive ashwagandha (Withania somnifera) root extract (ARE) 600 mg/day (n = 60)/identical placebo (n = 60) orally for 8 weeks. Cognitive function was assessed at baseline and week 8 using a Computerized Mental Performance Assessment System (COMPASS). Secondary outcomes were Profile of Mood States Abbreviated Version (POMS-A), Mental Fatigue Scale (MFS) and Behavior Rating Inventory of Executive Function-Adult (BRIEF-A) for effects on mood, mental fatigue and executive function, respectively, assessed at baseline, week 4 and 8. Greater improvement (p < .05) from baseline scores were seen with ARE as against placebo for COMPASS items episodic memory, working memory and accuracy of attention. ARE also improved the POMS-A, MFS and BRIEF-A scores from baseline suggesting an improvement in mood, vigor, and an increase in the executive functioning respectively with ARE. The herb was well tolerated and had a good patient compliance with no serious adverse events reported in either of the groups. This study suggests that a dose of 600 mg a day can improve cognition, energy, and mood in adults with self-reported cognitive and energy problems.

Objective assessment of cognitive fatigue: a bibliometric analysis

AimThe objective of this study was to gain insight into the nature of cognitive fatigue and to identify future trends of objective assessment techniques in this field.MethodsOne thousand and eighty-five articles were retrieved from the Web of Science Core Collection database. R version 4.3.1, VOSviewer 1.6.20, CiteSpace 6.2.R4, and Microsoft Excel 2019 were used to perform the analysis.ResultsA total of 704 institutes from 56 countries participated in the relevant research, while the People’s Republic of China contributed 126 articles and was the leading country. The most productive institute was the University of Gothenburg. Johansson Birgitta from the University of Gothenburg has posted the most articles (n = 13). The PLOS ONE published most papers (n = 38). The Neurosciences covered the most citations (n = 1,094). A total of 3,116 keywords were extracted and those with high frequency were mental fatigue, performance, quality-of-life, etc. Keywords mapping analysis indicated that cognitive fatigue caused by continuous work and traumatic brain injury, as well as its rehabilitation, have become the current research trend. The most co-cited literature was published in Sports Medicine. The strongest citation burst was related to electroencephalogram (EEG) event-related potential and spectral power analysis.ConclusionPublication information of related literature on the objective assessment of cognitive fatigue from 2007 to 2024 was summarized, including country and institute of origin, authors, and published journal, offering the current hotspots and novel directions in this field.

Long-term course and factors influencing work ability and return to work in post-COVID patients 12 months after inpatient rehabilitation

BackgroundRehabilitation plays a crucial role in restoring work ability and facilitating the reintegration of post-COVID patients into the workforce. The impact of rehabilitation on work ability and return to work (RTW) of post-COVID patients remains poorly understood. This study was conducted to assess the work ability and RTW of post-COVID patients before rehabilitation and 12 months after rehabilitation and to identify physical and neuropsychological health factors influencing RTW 12 months after rehabilitation.MethodsThis longitudinal observational study included 114 post-COVID patients with work-related SARS-CoV-2 infection who underwent inpatient post-COVID rehabilitation with indicative focus on pulmonology and/or psychotraumatology (interval between date of SARS-CoV-2 infection and start of rehabilitation: M = 412.90 days). Employment status, work ability, and the subjective prognosis of employment (SPE) scale were assessed before rehabilitation (T1) and 12 months after rehabilitation (T4). The predictors analysed at T4 were functional exercise capacity, physical activity, subjective physical and mental health status, fatigue, depression, and cognitive function. Longitudinal analyses were performed via the Wilcoxon signed-rank test. Logistic and linear regression analyses identified predictors of work ability and return to work (RTW), whereas mediation analyses examined the relationships between these predictors and work ability.ResultsAt T4, the median of WAI total score indicated poor work ability, which significantly worsened over time (p < 0.001; r = 0.484). The SPE scale significantly increased from T1 to T4 (p = 0.022, r = -0.216). A total of 48.6% of patients had returned to work 12 months after rehabilitation. Fatigue was identified as the main predictor of reduced work ability and RTW, with each unit increase in fatigue severity decreasing the odds of RTW by 3.1%. In addition, physical capacity and subjective health status were significant predictors of perceived work ability.ConclusionsThe findings highlight the significant challenges that post-COVID patients face in regaining work ability and achieving successful RTW 12 months after rehabilitation. Fatigue appears to be an important predictor of work ability and RTW. To optimize recovery and enhance both biopsychosocial health and work ability, it is crucial to develop and implement personalised interventions that address fatigue, improve physical capacity, and support mental health.Trial registrationThis study is registered in the German Clinical Trials Register under DRKS00022928.

Online Assessment of Spontaneous Mental Fatigue in Construction Workers Considering Data Quality: Improved Online Sequential Extreme Learning Machine

Online Assessment of Spontaneous Mental Fatigue in Construction Workers Considering Data Quality: Improved Online Sequential Extreme Learning Machine

Physiological Predictors of Operator Performance: The Role of Mental Effort and Its Link to Task Performance.

The present study investigated how pupil size and heart rate variability (HRV) can contribute to the prediction of operator performance. We illustrate how focusing on mental effort as the conceptual link between physiological measures and task performance can align relevant empirical findings across research domains. Physiological measures are often treated as indicators of operators' mental state. Thereby, they could enable a continuous and unobtrusive assessment of operators' current ability to perform the task. Fifty participants performed a process monitoring task consisting of ten 9-minute task blocks. Blocks alternated between low and high task demands, and the last two blocks introduced a task reward manipulation. We measured response times as primary performance indicator, pupil size and HRV as physiological measures, and mental fatigue, task engagement, and perceived effort as subjective ratings. Both increased pupil size and increased HRV significantly predicted better task performance. However, the underlying associations between physiological measures and performance were influenced by task demands and time on task. Pupil size, but not HRV, results were consistent with subjective ratings. The empirical findings suggest that, by capturing variance in operators' mental effort, physiological measures, specifically pupil size, can contribute to the prediction of task performance. Their predictive value is limited by confounding effects that alter the amount of effort required to achieve a given level of performance. The outlined conceptual approach and empirical results can guide study designs and performance prediction models that examine physiological measures as the basis for dynamic operator assistance.

Classification of recovery states in U15, U17, and U19 sub-elite football players: a machine learning approach.

A promising approach to optimizing recovery in youth football has been the use of machine learning (ML) models to predict recovery states and prevent mental fatigue. This research investigates the application of ML models in classifying male young football players aged under (U)15, U17, and U19 according to their recovery state. Weekly training load data were systematically monitored across three age groups throughout the initial month of the 2019-2020 competitive season, covering 18 training sessions and 120 observation instances. Outfield players were tracked using portable 18-Hz global positioning system (GPS) devices, while heart rate (HR) was measured using 1 Hz telemetry HR bands. The rating of perceived exertion (RPE 6-20) and total quality recovery (TQR 6-20) scores were employed to evaluate perceived exertion, internal training load, and recovery state, respectively. Data preprocessing involved handling missing values, normalization, and feature selection using correlation coefficients and a random forest (RF) classifier. Five ML algorithms [K-nearest neighbors (KNN), extreme gradient boosting (XGBoost), support vector machine (SVM), RF, and decision tree (DT)] were assessed for classification performance. The K-fold method was employed to cross-validate the ML outputs. A high accuracy for this ML classification model (73-100%) was verified. The feature selection highlighted critical variables, and we implemented the ML algorithms considering a panel of 9 variables (U15, U19, body mass, accelerations, decelerations, training weeks, sprint distance, and RPE). These features were included according to their percentage of importance (3-18%). The results were cross-validated with good accuracy across 5-fold (79%). The five ML models, in combination with weekly data, demonstrated the efficacy of wearable device-collected features as an efficient combination in predicting football players' recovery states.

Solutions to Adolescent Depression and Anxiety: A Exercise Based Perspective

As the pace of society continues to accelerate, the frequency of mental fatigue and emotional stress that people feel in their daily lives is becoming more frequent, which has caused the prevalence of depression and anxiety to rise rapidly and has now reached alarming levels. According to the World Health Organization, a staggering 13% of the global adolescent population has been diagnosed with depression and anxiety, a silent epidemic that casts a long shadow over our youth. Based on the above background, this paper first discusses the changing dynamics of the prevalence of depression and anxiety among young people and its negative effects on them. Subsequently, the therapeutic effects of exercise are analyzed in terms of accessibility, affordability, and potential as a complementary or alternative treatment. Finally, this paper gives some suggestions for better prevention of depression and anxiety.

Improving health workers’ well-being in Cittadella Hospital (Province of Padua)

Abstract Issue A healthy workplace increases productivity, creativity and decreases absenteeism and turn-over. It also contributes to creating a more secure work environment with fewer risks of violence. In the past 3 years, the healthcare system has suffered the psychological, economic and social consequences of the COVID-19 pandemic. On the other hand, the healthcare staff reductions determine high levels of work related stress that are often unsustainable. Description In an effort to improve staff well-being, in the Hospital of Cittadella, which counts nearly 1,250 employees, a wide range of activities have been initiated. A questionnaire was submitted to the hospital’s staff and the results showed that nearly 10% of workers had experienced physical symptomatology related to work. The most commonly experienced symptoms included: anxiety, nervousness, headache, stomach ache, excessive fatigue and insomnia. Participants also indicated feeling excessive mental fatigue and emotional overload at the end of their work shift. Results Psychomotor practice, held according to the Aucouturier method, is one of the projects intended especially for the staff operating in Intensive Care, Emergency and Pneumology Units. This method brings focus to controlled breathing, posture, muscle work and movement that help manage stress and fatigue. A Qigong course, which is an ancient Chinese practice designed to optimize the energy within the body reducing the stress levels and increasing general wellbeing, was held every two weeks for 5 months. And finally, Tibetan singing crystal bowls sessions consisted of monthly guided meditation sessions using the sounds of the crystal bowls. Lessons In conclusion, well-being and organizational performance are closely related to each other. It is crucial for any organization to encourage and maintain better physical and mental health of the healthcare staff as it directly affects productivity and consequently user’s satisfaction of the services provided. Key messages • Stress management is important amongst healthcare professionals as they are continuously exposed to different job stressors. • Promoting self awareness and self care can help create a healthier work environment.

Impact of Smartphone-Induced Mental Fatigue on Resistance Training Performance and Efficiency - The Role of Smartphone Use During Workout

Introduction Resistance training volume is a key determinant of muscle hypertrophy and strength development. However, mental fatigue can significantly impact this volume, ultimately affecting performance. One prominent source of mental fatigue in modern gym environments is smartphone use, which has become pervasive and may reduce workout efficiency and overall training volume. Purpose This review examines the dual effects of smartphone use on resistance training outcomes and offers strategies to balance these impacts effectively. Conclusions Smartphone-induced mental fatigue increases perceived exertion, leading to reduced performance during resistance training by lowering volume-load and endurance, particularly in low- and moderate-intensity exercises. Despite this, maximal strength appears to remain unaffected. Additionally, smartphone use diverts cognitive resources, resulting in mental fatigue and impairing both physical and technical performance due to distractions during workouts. It can also unintentionally prolong rest periods, which disrupts the balance between muscle recovery and mental readiness, further decreasing training efficiency. However, smartphones also offer valuable benefits, such as access to fitness apps, progress tracking, and motivational music, which can help maintain or even enhance performance by improving focus and motivation. To minimize distractions and optimize training outcomes, strategies such as using airplane mode or scheduling specific times for phone use are recommended. While excessive smartphone use can impair training efficiency, careful management and strategic use can enable athletes to capitalize on its benefits and improve resistance training results. Future research should focus on developing best practices for incorporating smartphone use in fitness settings to balance its advantages while minimizing its downsides.

Intelligent Human Operator Mental Fatigue Assessment Method Based on Gaze Movement Monitoring.

Modern mental fatigue detection methods include many parameters for evaluation. For example, many researchers use human subjective evaluation or driving parameters to assess this human condition. Development of a method for detecting the functional state of mental fatigue is an extremely important task. Despite the fact that human operator support systems are becoming more and more widespread, at the moment there is no open-source solution that can monitor this human state based on eye movement monitoring in real time and with high accuracy. Such a method allows the prevention of a large number of potential hazardous situations and accidents in critical industries (nuclear stations, transport systems, and air traffic control). This paper describes the developed method for mental fatigue detection based on human eye movements. We based our research on a developed earlier dataset that included captured eye-tracking data of human operators that implemented different tasks during the day. In the scope of the developed method, we propose a technique for the determination of the most relevant gaze characteristics for mental fatigue state detection. The developed method includes the following machine learning techniques for human state classification: random forest, decision tree, and multilayered perceptron. The experimental results showed that the most relevant characteristics are as follows: average velocity within the fixation area; average curvature of the gaze trajectory; minimum curvature of the gaze trajectory; minimum saccade length; percentage of fixations shorter than 150 ms; and proportion of time spent in fixations shorter than 150 milliseconds. The processing of eye movement data using the proposed method is performed in real time, with the maximum accuracy (0.85) and F1-score (0.80) reached using the random forest method.