Exploring workability in an older working population: associations with cognitive functioning, sleep quality, and technostress.

Objective: This observational study investigates workability and its associations with cognitive functioning, sleep quality and technostress among an older working population, also shedding light on potential differences between two occupational categories with different work schedules. Methods: Workers aged over 50, employed in different working sectors (banking/finance, chemical and metal-mechanic industry) were administered a self- report questionnaire including Work Ability Index (WAI), cognitive tests (Stroop Color Task, Corsi Blocks, Digit Span), sleep quality questionnaires (Pittsburgh Sleep Quality Index-PSQI; Insomnia Severity Index-ISI; Ford Insomnia Response to Stress Test-FIRST) and technostress scale. Linear regression models evaluated associations among variables, interaction effects investigated potential moderators. Results: A total of 468 aged workers categorized as white (WCWs; N = 289, 62%) or blue collars (BCWs; N = 179, 38%) were enrolled; most BCWs (N = 104; 58%) were night shift workers. WCWs reported higher workability, cognitive functioning, sleep quality and lower technostress (except for invasion and privacy subscales) than BCWs. Associations between cognitive functioning and workability were statistically significant only for BCWs [slopes equal to 0.2 (0.33), 0.8 (0.34), -0.02 (0.001) for Memory Span Corsi, Block Span Digit and Interference Speed respectively]; additionally, sleep quality significantly moderated this association (p = 0.007). Higher levels of technostress were associated with lower workability, and this relationship was stronger for BCWs. Conclusion: The aging of the workforce has important implications for occupational health and safety. Our findings suggest potential interventions and protective measures to promote older workers' wellbeing; blue-collar workers particularly should benefit from tailored intervention to sustain workability and prevent technostress, considering the role of healthy sleep habits promotion.

Combining Different Wearable Devices to Assess Gait Speed in Real-World Settings.

Assessing mobility in daily life can provide significant insights into several clinical conditions, such as Chronic Obstructive Pulmonary Disease (COPD). In this paper, we present a comprehensive analysis of wearable devices' performance in gait speed estimation and explore optimal device combinations for everyday use. Using data collected from smartphones, smartwatches, and smart shoes, we evaluated the individual capabilities of each device and explored their synergistic effects when combined, thereby accommodating the preferences and possibilities of individuals for wearing different types of devices. Our study involved 20 healthy subjects performing a modified Six-Minute Walking Test (6MWT) under various conditions. The results revealed only little performance differences among devices, with the combination of smartwatches and smart shoes exhibiting superior estimation accuracy. Particularly, smartwatches captured additional health-related information and demonstrated enhanced accuracy when paired with other devices. Surprisingly, wearing all devices concurrently did not yield optimal results, suggesting a potential redundancy in feature extraction. Feature importance analysis highlighted key variables contributing to gait speed estimation, providing valuable insights for model refinement.

The effects of work on cognitive functions: a systematic review.

Introduction: Cognitive functions play a crucial role in individual's life since they represent the mental abilities necessary to perform any activity. During working life, having healthy cognitive functioning is essential for the proper performance of work, but it is especially crucial for preserving cognitive abilities and thus ensuring healthy cognitive aging after retirement. The aim of this paper was to systematically review the scientific literature related to the effects of work on cognitive functions to assess which work-related factors most adversely affect them. Method: We queried the PubMed and Scopus electronic databases, in February 2023, according to the PRISMA guidelines (PROSPERO ID number = CRD42023439172), and articles were included if they met all the inclusion criteria and survived a quality assessment. From an initial pool of 61,781 papers, we retained a final sample of 64 articles, which were divided into 5 categories based on work-related factors: shift work (n = 39), sedentary work (n = 7), occupational stress (n = 12), prolonged working hours (n = 3), and expertise (n = 3). Results: The results showed that shift work, occupational stress, and, probably, prolonged working hours have detrimental effects on cognitive functioning; instead, results related to sedentary work and expertise on cognitive functions are inconclusive and extremely miscellaneous. Discussion: Therefore, workplace health and well-being promotion should consider reducing or rescheduling night shift, the creation of less demanding and more resourceful work environments and the use of micro-breaks to preserve workers' cognitive functioning both before and after retirement. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023439172, identifier CRD42023439172.

Report from a Tibetan Monastery: EEG neural correlates of concentrative and analytical meditation.

The positive effects of meditation on human wellbeing are indisputable, ranging from emotion regulation improvement to stress reduction and present-moment awareness enhancement. Changes in brain activity regulate and support these phenomena. However, the heterogeneity of meditation practices and their cultural background, as well as their poor categorization limit the generalization of results to all types of meditation. Here, we took advantage of a collaboration with the very singular and precious community of the Monks and Geshes of the Tibetan University of Sera-Jey in India to study the neural correlates of the two main types of meditation recognized in Tibetan Buddhism, namely concentrative and analytical meditation. Twenty-three meditators with different levels of expertise underwent to an ecological (i.e., within the monastery) EEG acquisition consisting of an analytical and/or concentrative meditation session at "their best," and with the only constraint of performing a 5-min-long baseline at the beginning of the session. Time-varying power-spectral-density estimates of each session were compared against the baseline (i.e., within session) and between conditions (i.e., analytical vs. concentrative). Our results showed that concentrative meditation elicited more numerous and marked changes in the EEG power compared to analytical meditation, and mainly in the form of an increase in the theta, alpha and beta frequency ranges. Moreover, the full immersion in the Monastery life allowed to share the results and discuss their interpretation with the best scholars of the Monastic University, ensuring the identification of the most expert meditators, as well as to highlight better the differences between the different types of meditation practiced by each of them.

The fear of spiders: perceptual features assessed in augmented reality.

Background: Persons with specific phobias typically generalize the dangerousness of the phobic animal to all members of its species, possibly as a result of malfunctioning brain circuitry normally providing quick and dirty identification of evolutionary-relevant stimuli. An objective assessment of which perceptual features make an animal more or less scary to phobic and non-phobic people would help overcome the limitations of the few studies available so far, based on self-reports. Objective: To achieve this aim, we built an augmented reality setting where volunteers with different levels of fear of spiders were asked to make holographic spiders that look either dangerous or harmless. To reach this goal, a computerized interface allowed participants to modify the spider's perceptual features (hairiness, body/leg size, and locomotion) in real time. Results: On average, the dangerous spiders were made hairy, thick, and moving according to spider-like locomotion; coherently, the harmless spiders were made hairless, slim, and moving according to a butterfly-like locomotion. However, these averaged preferences could not fully describe the complex relationship between perceptual preferences with each other and with arachnophobia symptoms. An example of a key finding revealed by cluster analysis is the similarity in perceptual preferences among participants with little or no fear of spiders, whereas participants with more arachnophobia symptoms expressed more varying preferences. Conclusion: Perceptual preferences toward the spider's features were behaviorally assessed through an observational study, objectively confirming a generalization effect characterizing spider-fearful participants. These results advance our knowledge of phobic preferences and could be used to improve the acceptability of exposure therapies.

Optimal social distancing in epidemic control: cost prioritization, adherence and insights into preparedness principles.

The COVID-19 pandemic experience has highlighted the importance of developing general control principles to inform future pandemic preparedness based on the tension between the different control options, ranging from elimination to mitigation, and related costs. Similarly, during the COVID-19 pandemic, social distancing has been confirmed to be the critical response tool until vaccines become available. Open-loop optimal control of a transmission model for COVID-19 in one of its most aggressive outbreaks is used to identify the best social distancing policies aimed at balancing the direct epidemiological costs of a threatening epidemic with its indirect (i.e., societal level) costs arising from enduring control measures. In particular, we analyse how optimal social distancing varies according to three key policy factors, namely, the degree of prioritization of indirect costs, the adherence to control measures, and the timeliness of intervention. As the prioritization of indirect costs increases, (i) the corresponding optimal distancing policy suddenly switches from elimination to suppression and, finally, to mitigation; (ii) the "effective" mitigation region-where hospitals' overwhelming is prevented-is dramatically narrow and shows multiple control waves; and (iii) a delicate balance emerges, whereby low adherence and lack of timeliness inevitably force ineffective mitigation as the only accessible policy option. The present results show the importance of open-loop optimal control, which is traditionally absent in public health preparedness, for studying the suppression-mitigation trade-off and supplying robust preparedness guidelines.

Digital Phenotyping for Monitoring Mental Disorders: Systematic Review.

BACKGROUND: The COVID-19 pandemic has increased the impact and spread of mental illness and made health services difficult to access; therefore, there is a need for remote, pervasive forms of mental health monitoring. Digital phenotyping is a new approach that uses measures extracted from spontaneous interactions with smartphones (eg, screen touches or movements) or other digital devices as markers of mental status. OBJECTIVE: This review aimed to evaluate the feasibility of using digital phenotyping for predicting relapse or exacerbation of symptoms in patients with mental disorders through a systematic review of the scientific literature. METHODS: Our research was carried out using 2 bibliographic databases (PubMed and Scopus) by searching articles published up to January 2023. By following the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) guidelines, we started from an initial pool of 1150 scientific papers and screened and extracted a final sample of 29 papers, including studies concerning clinical populations in the field of mental health, which were aimed at predicting relapse or exacerbation of symptoms. The systematic review has been registered on the web registry Open Science Framework. RESULTS: We divided the results into 4 groups according to mental disorder: schizophrenia (9/29, 31%), mood disorders (15/29, 52%), anxiety disorders (4/29, 14%), and substance use disorder (1/29, 3%). The results for the first 3 groups showed that several features (ie, mobility, location, phone use, call log, heart rate, sleep, head movements, facial and vocal characteristics, sociability, social rhythms, conversations, number of steps, screen on or screen off status, SMS text message logs, peripheral skin temperature, electrodermal activity, light exposure, and physical activity), extracted from data collected via the smartphone and wearable wristbands, can be used to create digital phenotypes that could support gold-standard assessment and could be used to predict relapse or symptom exacerbations. CONCLUSIONS: Thus, as the data were consistent for almost all the mental disorders considered (mood disorders, anxiety disorders, and schizophrenia), the feasibility of this approach was confirmed. In the future, a new model of health care management using digital devices should be integrated with the digital phenotyping approach and tailored mobile interventions (managing crises during relapse or exacerbation).

Artificial Intelligence Algorithms for Benign vs. Malignant Dermoscopic Skin Lesion Image Classification.

In recent decades, the incidence of melanoma has grown rapidly. Hence, early diagnosis is crucial to improving clinical outcomes. Here, we propose and compare a classical image analysis-based machine learning method with a deep learning one to automatically classify benign vs. malignant dermoscopic skin lesion images. The same dataset of 25,122 publicly available dermoscopic images was used to train both models, while a disjointed test set of 200 images was used for the evaluation phase. The training dataset was randomly divided into 10 datasets of 19,932 images to obtain an equal distribution between the two classes. By testing both models on the disjoint set, the deep learning-based method returned accuracy of 85.4 ± 3.2% and specificity of 75.5 ± 7.6%, while the machine learning one showed accuracy and specificity of 73.8 ± 1.1% and 44.5 ± 4.7%, respectively. Although both approaches performed well in the validation phase, the convolutional neural network outperformed the ensemble boosted tree classifier on the disjoint test set, showing better generalization ability. The integration of new melanoma detection algorithms with digital dermoscopic devices could enable a faster screening of the population, improve patient management, and achieve better survival rates.

Enhanced Myocardial Adenylyl Cyclase Activity Alters Heart-Brain Communication.

BACKGROUND: The central nervous system's influence on cardiac function is well described; however, direct evidence for signaling from heart to brain remains sparse. Mice with cardiac-selective overexpression of adenylyl cyclase type 8 (TGAC8) display elevated heart rate/contractility and altered neuroautonomic surveillance. OBJECTIVES: In this study the authors tested whether elevated adenylyl cyclase type 8-dependent signaling at the cardiac cell level affects brain activity and behavior. METHODS: A telemetry system was used to record electrocardiogram (ECG) and electroencephalogram (EEG) in TGAC8 and wild-type mice simultaneously. The Granger causality statistical approach evaluated variations in the ECG/EEG relationship. Mouse behavior was assessed via elevated plus maze, open field, light-dark box, and fear conditioning tests. Transcriptomic and proteomic analyses were performed on brain tissue lysates. RESULTS: Behavioral testing revealed increased locomotor activity in TGAC8 that included a greater total distance traveled (+43%; P < 0.01), a higher average speed (+38%; P < 0.01), and a reduced freezing time (-45%; P < 0.01). Dual-lead telemetry recording confirmed a persistent heart rate elevation with a corresponding reduction in ECG-R-waves interval variability and revealed increased EEG-gamma activity in TGAC8 vs wild-type. Bioinformatic assessment of hippocampal tissue indicated upregulation of dopamine 5, gamma-aminobutyric acid A, and metabotropic glutamate 1/5 receptors, major players in gamma activity generation. Granger causality analyses of ECG and EEG recordings showed a marked increase in informational flow between the TGAC8 heart and brain. CONCLUSIONS: Perturbed signals arising from the heart cause changes in brain activity, altering mouse behavior. More specifically, the brain interprets augmented myocardial humoral/functional output as a "sustained exercise-like" situation and responds by activating central nervous system output controlling locomotion.

Tumor-Infiltrating Lymphocyte Recognition in Primary Melanoma by Deep Learning Convolutional Neural Network.

The presence of tumor-infiltrating lymphocytes (TILs) is associated with a favorable prognosis of primary melanoma (PM). Recently, artificial intelligence (AI)-based approach in digital pathology was proposed for the standardized assessment of TILs on hematoxylin and eosin-stained whole slide images (WSIs). Herein, the study applied a new convolution neural network (CNN) analysis of PM WSIs to automatically assess the infiltration of TILs and extract a TIL score. A CNN was trained and validated in a retrospective cohort of 307 PMs including a training set (237 WSIs, 57,758 patches) and an independent testing set (70 WSIs, 29,533 patches). An AI-based TIL density index (AI-TIL) was identified after the classification of tumor patches by the presence or absence of TILs. The proposed CNN showed high performance in recognizing TILs in PM WSIs, showing 100% specificity and sensitivity on the testing set. The AI-based TIL index correlated with conventional TIL evaluation and clinical outcome. The AI-TIL index was an independent prognostic marker associated directly with a favorable prognosis. A fully automated and standardized AI-TIL appeared to be superior to conventional methods at differentiating the PM clinical outcome. Further studies are required to develop an easy-to-use tool to assist pathologists to assess TILs in the clinical evaluation of solid tumors.

Promoting health and productivity among ageing workers: a longitudinal study on work ability, biological and cognitive age in modern workplaces (PROAGEING study).

BACKGROUND: Large changes in ageing population and in retirement age are increasing the number of older people in the workforce, raising many challenges for policymakers in promoting employment opportunities and health for older workers. In this respect, longitudinal assessments of workability, well-being perception and cognitive skills over time may allow to detect factors influencing workers' health. Moreover, new available molecular markers permit the measurement of biological age and age-related changes. Most studies analysed one aspect at time (psychological, biological, labour productivity), without considering their interaction. Aims of the study are to evaluate the relationship between workability, cognitive skills, and biological age in a population of ageing workers; to conduct a cross-sectional analysis to assess the impact of occupational exposures on workability, cognitive skills, and biological age; to evaluate inter-individuals changes in a prospective analysis with a re-evaluation of each worker. METHODS: Our study plans to enrol 1000 full-time workers, aged over 50, undergoing the medical surveillance required by the current Italian Legislation. Data collection includes information about: (a) work ability and psychosocial risk factors (work ability index, HSE Management Standard-21 item, Utrecht Work Engagement Scale, World Health Organisation-Five, Well-Being Index, job satisfaction, general well-being, technostress); (b) cognitive skills (Stroop Color and Word test, Simon task, Corsi's block-tapping test, Digit span test); (c) sleep habits and psychological well-being (Pittsburgh Sleep Quality Index, Insomnia Severity Index, Ford Insomnia Response to Stress Test; Symptom Check List 90, Psychological Well-Being Index, Profile of Mood State, Beck Depression Inventory, Beck Anxiety Inventory, Perceived Stress Scale, Brief COPE); (d) biological age (telomere length, DNA methylation) for 500 workers. All workers will repeat the evaluation after one year. DISCUSSION: This study aims to increase our knowledge about interactions between work ability, cognitive ability, well-being perception and psychological status also by including molecular markers, with a longitudinal and multidisciplinary approach. By bringing better insights into the relationship between risk factors and their impact on perceived and biological health, this study also aims at identifying possible interventions and protective measures to ensure aged workers' well-being, consistent with all the eminent calls for actions promoted by key International and European labour organizations.

Meta-analytic study on substance intake and work-related accidents calls for attention to bio-psycho-social factors.

Accidents at work are a major concern because of their social and economic impact. The causes are highly variable and often linked to risk behaviors that could be avoided, of which substance use is a prime example. The aim of this paper was to meta-analytically review the scientific literature on substance intake and its link to work-related accidents. From an initial pool of 19954 papers, we considered a final sample of 27 clustered in three groups according to substances class (alcohol, recreational drugs, medicines). Despite different pharmacological effects, substances consumed for recreational purposes significantly increased the risk of work-related accidents (odds ratio: alcohol 1.78, recreational drugs 1.47), whereas medicines did not: however, these results require caution due to the heterogeneity of the included studies and suspected publication bias. While bio-psycho-social factors could have helped to understand this association, selected studies neglected both the variegated effects and the root causes of recreational substance consumption. Future studies and interventions should consider these complexity factors to transcend the mere description of the phenomenon.

An Innovative Sensorized Face Mask for Early Detection of Physiological Changes Associated with Viral Infection.

A sensorized face mask could be a useful tool in the case of a viral pandemic event, as well as the Covid-19 emergency. In the context of the proposed project "RESPIRE", we have developed a "Smart-Mask" able to collect the signal patterns of body temperature, respiration, and symptoms such as cough, through a set of textile sensors. The signals have been analyzed by Artificial Intelligence algorithms in order to compare them with gold standard measurements, and to recognize the physiological changes associated with a viral infection. This low-cost prototype of a smart face mask is a reliable tool for the estimation of the individual physiological parameters. Moreover, it enables both personal protection and the early and rapid identification and tracking of potentially infected individuals.

Low cardiac frequency associated with higher number of extrasistoles in a computational model of Brugada Syndrome.

Brugada Syndrome is a form of idiopathic ventricular fibrillation, to date there is no definitive theory about how ventricular fibrillation is initiated or its substrate. Starting from the clinical observation that cardiac episodes are more frequent at rest, we developed a model in order to study the effect of cardiac frequency on reentrant activity. Our results suggest that the combination of arrhythmic substrate and cardiac frequency has a role in the insurgence of cardiac arrhythmia.

Exploiting Resistive Matrix Technology to Build a Stretchable Sensorised Sock for Gait Analysis in Daily Life.

We describe the development and preliminary evaluation of an innovative low-cost wearable device for gait analysis. We have developed a sensorized sock equipped with 32 piezoresistive textile-based sensors integrated in the heel and metatarsal areas for the detection of signals associated with the contact pressures generated during walking phases. To build the sock, we applied a sensing patch on a commercially available sock. The sensing patch is a stretchable circuit based on the resistive matrix method, in which conductive stripes, based on conductive inks, are coupled with piezoresistive fabrics to form sensing elements. In our sensorized sock, we introduced many relevant improvements to overcome the limitations of the classical resistive matrix method. We preliminary evaluated the sensorized sock on five healthy subjects by performing a total of 80 walking tasks at different speeds for a known distance. Comparison of step count and step-to-step frequency versus reference measurements showed a high correlation between the estimated measure and the real one.

A Systematic Review on the Role of Substance Consumption in Work-Related Road Traffic Crashes Reveals the Importance of Biopsychosocial Factors in Prevention.

OBJECTIVE: Since many jobs imply driving, a relevant part of all road traffic crashes (RTC) is related to work. Statistics considering all crashes suggest that they are significantly associated with consumption of substances, but the root causes are not yet clear. The objective of the present paper was to systematically review the scientific literature concerning substances consumption and work-related RTC. We queried the PubMed and Scopus electronic databases according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Articles were included if they reported all necessary data and survived a quality assessment. We selected a final sample of 30 articles from an initial pool of 7113. As hypothesized, taking any of the considered substances was found to increase the risk of work-related RTC. Descriptive statistics on work-related RTC showed a higher average positivity rate for medicines (14.8%) than for alcohol (3.02%) and drugs (0.84%). Interestingly, the impact of some medications found an unconvincing explanation in the mere occurrence of side effects, and it suggests that psychosocial and/or medical conditions could be better predictors of RTC. We therefore propose an intervention and prevention model that also considers biopsychosocial factors, for which further studies are needed in future research.

Sport in Town: The Smart Healthy ENV Project, a Pilot Study of Physical Activity with Multiparametric Monitoring.

BACKGROUND: Increasing evidence links meteorological characteristics and air pollution to physiological responses during sports activities in urban areas with different traffic levels. OBJECTIVE: The main objective of the Smart Healthy ENV (SHE, "Smart Monitoring Integrated System For A Healthy Urban Environment In Smart Cities") project was to identify the specific responses of a group of volunteers during physical activity, by monitoring their heart rates and collecting breath samples, combined with data on meteorological determinants and pollution substances obtained through fixed sensor nodes placed along city routes and remotely connected to a dedicated data acquisition server. METHODS: Monitoring stations were placed along two urban routes in Pisa, each two km long, with one located within the park beside the Arno river (green route) and the other in a crowded traffic zone (red route). Our sample participants were engaged in sports activities (N = 15, with different levels of ability) and were monitored through wearable sensors. They were first asked to walk back and forth (4 km) and then to run the same route. The experimental sessions were conducted over one day per route. A breath sample was also collected before each test. A questionnaire concerning temperature and fatigue perception was administered for all of the steps of the study over the two days. RESULTS: The heart rates of the participants were monitored in the baseline condition, during walking, and while running, and were correlated with meteorological and pollutant data and with breath composition. Changes in the heart rates and breath composition were detected during the experimental sessions. These variations were related to the physical activity and to the meteorological conditions and air pollution levels. CONCLUSIONS: The SHE project can be considered a proof-of-concept study aimed at monitoring physiological and environmental variables during physical activity in urban areas, and can be used in future studies to provide useful information to those involved in sports and the broader community.

Attention-Dependent Physiological Correlates in Sleep-Deprived Young Healthy Humans.

Cognitive functions could be specifically altered but masked from the unspecific effect of workload, a common factor affecting cognitive functions that modulate peripheral outputs. To identify workload-related and specific, task-dependent components, physiological correlates of cognitive functioning were derived by studying 15 healthy volunteers performing attentional tasks in baseline and post-sleep-deprivation conditions (one week interval). Sleep deprivation was introduced to increase workload. We performed recordings of heart pulse, facial temperature, and head movements during tasks assessing attentional network efficiency (ANT, Attentional Network Task; CCT, Continuous Compensatory Tracker) workload assessments after execution of tasks. Changes in cognitive and physiological indices were studied in both conditions; physiological correlates of cognitive performance were identified by correlating changes from baseline to post-sleep-deprivation condition of task indices with those of physiological measures after correction for between-conditions workload changes. We found that mental and physical demands of workload increased after sleep deprivation. We identified no changes in cognitive and physiological indices across conditions; specific physiological correlates of attentional systems, as indicated by the negative correlation between changes in ANT-alerting and changes in amplitude of head movements and the positive correlation between changes in CCT-speed indexing alertness and changes in facial temperature.