Human Vigilance Research Articles

Light Exposure on Alertness after Wake-Up in Healthy Men: Comparing Dim, Bright, Red, and Blue Light

Introduction: Light is a key factor in moderating human alertness, both subjective and objective. However, the methodology applies in research on the effects of exposure to light of different wavelengths and intensities on objective and subjective alertness varies greatly and evidence on objective alertness in particular is still inconclusive. Thus, the present, highly standardized within-subject laboratory study on N = 44 healthy males explored how LED light of different intensities (dim vs. bright light) and wavelengths (red vs. blue) affected objective (reaction time/RT) as well as subjective (sleepiness) alertness in the morning after wake-up. Methods: Participants spent two separate nights in the laboratory and were exposed to either one of the two light intensities or colors for 60 min after wake-up. Additionally, they indicated their sleepiness on the Karolinska Sleepiness Scale and participated in an auditory RT task before and after light intervention. It was hypothesized that both bright and blue light would lead to greater subjective and objective alertness when compared to dim and red light, respectively. Results: Results indicated that average RTs were longer for participants in the bright light condition (p = 0.004, f2 = 0.07) and that RTs decreased post-light exposure irrespective of light being dim or bright (p = 0.026, f2 = 0.07). However, dim versus bright light and RT did not interact (p = 0.758, f2 = 0.07). Chronotype was a significant covariate in the interaction of dim versus bright light and subjective sleepiness (p = 0.008, f2 = 0.22). There was no difference in RTs when comparing exposure to red or blue light (p = 0.488, f2 = 0.01). Findings on subjective sleepiness and light of different wavelengths revealed that sleepiness was reduced after light exposure (p = 0.007, f2 = 0.06), although the wavelength of light did not appear to play a role in this effect (p = 0.817, f2 = 0.06). Conclusion: Hence, neither of the hypotheses could be confirmed. However, they indicated that evening types might benefit from exposure to bright light regarding sleepiness, but not morning types.

Hubungan Antara Kelelahan Dengan Tingkat Kecemasan Perawat Rumah Sakit: Sebuah Tinjauan Pustaka

Fatigue can be caused by overwork, prolonged physical and mental activity, lack of rest, high stress or a combination of these factors. Work fatigue is caused by tiring and energy-draining activities, thereby reducing human alertness and response to stress. Anxiety is a common emotional disorder characterized by deep and persistent fear or worry, but without any disturbance in the assessment of reality. A nurse is someone who has graduated from a nursing school, both inside and outside of school, in accordance with the provisions of applicable laws and regulations. This article provides an explanation of work fatigue, anxiety and determines the relationship between anxiety and work fatigue specifically for nurses who work in hospitals. This research uses a qualitative approach research methodology by collecting data using structured interviews with 2 research subjects, namely nurses in the Emergency Department and Inpatient Installation who work in private hospitals in Wonogiri Regency accompanied by a literature review based on the literature. Based on literature sources, it was found that high work fatigue can cause an increased risk of anxiety disorders up to 2.7 times higher compared to subjects with lower work fatigue. From the results of interviews with the 2 research subjects, it was found that the level of work fatigue was positively related to anxiety, meaning that the higher the level of work fatigue based on the scoring of the Job Fatigue Measuring Tool Questionnaire (KAUPK2), the higher the anxiety level score based on the Hamilton Anxiety Rating Scale.

Diurnal biological effects of correlated colour temperature and its exposure timing on alertness, cognition, and mood in an enclosed environment

Artificial lighting, which profits from the non-visual effects of light, is a potentially promising solution to support residents’ psychophysiological health and performance at specific times of the day in enclosed environments. However, few studies have investigated the non-visual effects of daytime correlated colour temperature (CCT) and its exposure timing on human alertness, cognition, and mood. However, the neural mechanisms underlying these effects are largely unknown. The current study evaluated the effects of daytime CCT and its exposure timing on markers of subjective experience, cognitive performance, and cerebral activity in a simulated enclosed environment. Forty-two participants participated a single-blind laboratory study with a 4 within (CCT: 4000 K vs. 6500 K vs. 8500 K vs. 12,000 K) × 2 between (exposure timing: morning vs. afternoon) mixed design. The results showed time of the day dependent benefits of the daytime CCT on subjective experience, vigilant attention, response inhibition, working memory, emotional perception, and risk decisions. The results of the electroencephalogram (EEG) revealed that lower-frequency EEG bands, including theta, alpha, and alpha-theta, were quite sensitive to daytime CCT intervention, which provides a valuable reference for trying to establish the underlying mechanisms that support the performance-enhancement effects of exposure to CCT in the daytime. However, the results revealed no consistent intervention pattern across these measurements. Therefore, future studies should consider personalised optimisation of daytime CCT for different cognitive demands.

VigilEye: Machine learning-powered driver fatigue recognition for safer roads

In an era where autonomous vehicles are on the horizon, the importance of human vigilance during driving cannot be understated. One of the paramount challenges road safety advocates face is driver fatigue, a silent culprit behind many tragic accidents. Our project seeks to address this issue by merging facial feature recognition with cutting-edge machine learning techniques, harnessing tools such as OpenCV and Dlib. This approach is centred around 68 precise facial feature detectors, adept at capturing specific markers like the status of a driver's eyes. Once data is acquired, our algorithms scrutinize it for fatigue indicators. Offering both cost and user benefits, our non-intrusive system swiftly alerts drivers, through auditory or tactile means, upon detecting drowsiness. Our system achieved a remarkable 94 % efficiency in timely and accurate fatigue detection through exhaustive testing across varied scenarios, underscoring its potential to revolutionize road safety.

The non-visual effects of correlated color temperature on the alertness, cognition, and mood of fatigued individuals during the afternoon

Railway dispatchers are prone to mental fatigue due to prolonged periods of intense concentration. As the main or even the only light source in the enclosed control centers, artificial lighting has non-visual effects on human alertness, cognition, and mood. To investigate whether external environmental cues could counteract performance decline induced by endogenous cardiac exhaustion, the current study modulated four correlated color temperature (CCT) levels and developed one visual task and six cognitive tasks representing basic and advanced cognitive functions, including sustained attention, response inhibition, working memory, risk decision-making, executive control, and emotion perception. A within-subjects design was employed to collect subjective and behavioral responses under both normal and fatigued mental antecedent states. Electroencephalogram (EEG) with alpha and theta bands as well as four fatigue-related algorithms including θ/β, α/β, (θ+α)/β, and (θ+α)/(α+β) were analyzed to explore the underlying neural mechanisms behind these responses. The results indicated a complex interactive pattern of CCT and mental antecedent state on alertness, cognition, and mood. Higher CCT had a supportive effect on subjective alertness and positive mood, independent of mental antecedent state. However, it exhibited a slight performance-impairing effect on sustained attention tasks. Conversely, higher CCT demonstrated a significant enhancement in advanced cognitive functions for fatigued individuals. EEG data revealed alpha oscillations increased, but theta activity and (θ + α)/β suppressed at 12,000 K, suggesting higher CCT partially alleviated the decline in alertness and cognition induced by mental fatigue. To develop an appropriate photobiological lighting scheme for fatigue intervention, larger and longer-term studies are needed in the future to measure a range of confounding factors and individual differences.

Driver body condition monitoring system based on human-computer interaction

Tired driving is still a significant cause of traffic accidents, often causing huge economic losses to society.Therefore, how to avoid driver fatigue has become a meaningful problem. The purpose of this paper is to review and summarize various research methods of driver fatigue monitoring system at home and abroad, so as to reduce the probability of traffic accidents caused by fatigue driving. The main content of this paper is to review the existing fatigue driving monitoring technologies such as electrocardiogram (ECG), electroencephalogram (EEG), HRV, eye tracking system, CNN, facial state analysis, emotion recognition, 5G and brain wave recognition, and infer the fatigue level of drivers by using these technologies to extract various clues that usually represent the level of human vigilance. Assess cognitive load and identify emotional states to monitor tired driving. By discussing the advantages and disadvantages of various fatigue monitoring systems at home and abroad, this paper proposes an innovative method, which transforms the previous single-mode monitoring system into a multi-mode monitoring system, integrates multiple biosensors, extracts relevant features from the biosensor data and processes the data reasonably in order to understand the drivers physiological state more comprehensively. This method is expected to improve the accuracy of fatigue monitoring system.

A scoping review of olfactory interventions for fatigue relief: addressing occupational health hazards.

Fatigue poses risks to occupational health and safety, affecting individuals' work efficiency, physical health, and social security, as well as human wellbeing and quality of life. Olfactory interventions, due to their low interference, are considered promising strategies for mitigating fatigue and reducing occupational health hazards. The objective of this review is to bridge the current gaps in the literature by conducting a scoping review of olfactory interventions on human alertness. It aims to explore their application in various occupational settings and to provide comprehensive and practical guidance for the practical application of olfactory interventions in mitigating fatigue and reducing occupational risks. The literature research was conducted in English using electronic databases such as Web of Science. Keywords related to scent and fatigue and the review followed PRISMA Extension for Scoping Reviews and PICO framework. 28 studies were included in this work. Participant characteristics, fatigue measurement methods, and scent intervention methods, such as types of scents, intervention strategies, and scent presentation systems, are thoroughly investigated and discussed. Additionally, the study places a specific emphasis on the applications and research within the field of scent interventions for fatigue driving. Olfactory interventions have been applied to populations in various occupational fields, demonstrating beneficial effects on both physiological and psychological fatigue. Olfactory intervention is effective and promising for enhancing alertness and improving the occupational environment. To provide detailed and practical guidance for the actual application of olfactory intervention in fatigue relief and reducing occupational health and safety hazards, further research into the potential mechanisms, applications, and efficacy assessment systems of fatigue-related olfactory interventions is necessary.

CsXDH1 gene promotes caffeine catabolism induced by continuous strong light in tea plant.

Tea plant (Camellia sinensis) is an important cash crop with extensive adaptability in the world. However, complex environmental factors force a large variation of tea quality-related components. Caffeine is essential for the formation of bitter and fresh flavors in tea, and is the main compound of tea that improves human alertness. Continuous strong light stimulation was observed to cause caffeine reduction in tea leaves, but the mechanism is not clear. In this study, the response of tea plant to light intensity was analysed mainly by multi-omics association, antisense oligodeoxynucleotide (asODN) silencing technique, and in vitro enzyme activity assay. The results revealed multiple strategies for light intensity adaptation in tea plant, among which the regulation of chloroplasts, photosynthesis, porphyrin metabolism, and resistance to oxidative stress were prominent. Caffeine catabolism was enhanced in continuous strong light, which may be a light-adapted strategy due to strict regulation by xanthine dehydrogenase (XDH). asODN silencing and enzymatic activity assays confirmed that CsXDH1 is a protein induced by light intensity to catalyze the substrate xanthine. CsXDH1 asODN silencing resulted in significant up-regulation of both caffeine and theobromine in in vitro enzyme activity assay, but not in vivo. CsXDH1 may act as a coordinator in light intensity adaptation, thus disrupting this balance of caffeine catabolism.

Experimental performance of smart IoT-enabled drip irrigation system using and controlled through web-based applications

The water requirements in irrigation have been growing and the accurate quantity of water can be produced by a smart irrigation system. Considering this kind of need, this paper aims to develop an Internet of Things (IoT) enabled smart drip irrigation system by applying Web/Android applications that will provide a solution for continuous monitoring and controlling the drip irrigation system to avoid the problems of constant human vigilance and waste of water. It also facilitates prevention by giving automatic water to plants relying on water necessities. It can also convince be capable in Agricultural fields, Parks, Lawns, etc. With the advancement of technology, there are always reducing risks and making work simpler. The embedded system provides a solution for solving this kind of problem. In this paper, a smart drip irrigation system is established which is driven by IoT and web-based applications. The web application is also designed for taking appropriate action for the user during drip irrigation. This application provides the appropriate amount of water from the pump for gardening. It can be accomplished by incorporating different sensors within the system to observe the humidity, temperature, and soil moisture conditions which transmit the data to the micro-controller for proper estimating the water needs of the plants. This kind of system can be controlled and visualized in the android mobile phone through a web application anywhere.

Nocturnal sodium oxybate increases the anterior cingulate cortex magnetic resonance glutamate signal upon awakening.

Clinical guidelines recommend sodium oxybate (SXB; the sodium salt of γ-hydroxybutyrate) for the treatment of disturbed sleep and excessive daytime sleepiness in narcolepsy, yet the underlying mode of action is elusive. In a randomised controlled trial in 20 healthy volunteers, we aimed at establishing neurochemical changes in the anterior cingulate cortex (ACC) following SXB-enhanced sleep. The ACC is a core neural hub regulating vigilance in humans. At 2:30 a.m., we administered in a double-blind cross-over manner an oral dose of 50 mg/kg SXB or placebo, to enhance electroencephalography-defined sleep intensity in the second half of nocturnal sleep (11:00 p.m. to 7:00 a.m.). Upon scheduled awakening, we assessed subjective sleepiness, tiredness and mood and measured two-dimensional, J-resolved, point-resolved magnetic resonance spectroscopy (PRESS) localisation at 3-Tesla field strength. Following brain scanning, we used validated tools to quantify psychomotor vigilance test (PVT) performance and executive functioning. We analysed the data with independent t tests, false discovery rate (FDR) corrected for multiple comparisons. The morning glutamate signal (at 8:30 a.m.) in the ACC was specifically increased after SXB-enhanced sleep in all participants in whom good-quality spectroscopy data were available (n=16; pFDR < 0.002). Further, global vigilance (10th-90th inter-percentile range on the PVT) was improved (pFDR < 0.04) and median PVT response time was shorter (pFDR < 0.04) compared to placebo. The data indicate that elevated glutamate in the ACC could provide a neurochemical mechanism underlying SXB's pro-vigilant efficacy in disorders of hypersomnolence.

Emerging order of anomalous eye movements with progressive drowsiness.

It has been widely recognized that human alertness is reflected in the eyes (e.g., when drowsiness, miosis, slow saccades, divergence, less compensatory vestibulo-ocular reflex, and less-accurate optokinetic response and smooth pursuit emerge). Previous studies that discovered these pupil/oculomotor anomalous behaviors along with lowering alertness evaluated only one or a few of them simultaneously, thus their emergence order is yet unknown. Presently, we focused on the following five pupil/oculomotor behaviors that can be evaluated under a natural stationary environment without giving external sensory stimulations: saccades, slow-phase eye movements, vergence, pupil diameter, and blinks. We demonstrate that their anomalous behaviors emerge in the following order: first: frequent saccades; second: slow saccades; third: divergence & miosis, then slow eye movement, while elongated eyelid closure duration emerges randomly in this sequence. These results provide a basis for the oculo-pupillometry-enabling objective monitoring of progressive drowsiness.

Arduino-based vehicle collision detection and warning system

As the number of vehicles increases day by day, accidents are also rapidly increasing. This surge in accidents poses a significant challenge for road safety authorities, necessitating innovative solutions and stricter enforcement of traffic regulations. Addressing the root causes, such as driver education and infrastructure improvements, is crucial to mitigating the escalating risks on our roads. These accidents can occur due to false estimation of nearby vehicles, disturbances in the mind of the driver, or any other reasons that prevent the driver from maintaining focus on driving. Therefore, not only is the accurate estimation of the distance to other surrounding vehicles necessary, but quick actions are also required to avoid any kind of accidents. In addition, advancements in technology, such as the integration of automated driving assistance systems, aim to enhance the precision of distance estimation and mitigate the risk of accidents caused by human errors. As the automotive industry continues to innovate, the intersection of human vigilance and technological support becomes crucial for ensuring road safety. This paper is specifically focused on preventing accidents. The system is designed to measure the distance between the driving car and the front object. If the driver fails to maintain the minimum safety distance from the front object, the system will warn the driver to slow down the speed of the car and avoid a collision. The driver will receive both visual and audio warnings to ensure that a collision does not occur. Additionally, the paper incorporates advanced sensor technologies and real-time data analysis to enhance the accuracy of distance measurements, providing a robust and reliable solution for accident prevention.

Development of a biomathematical model for human alertness and fatigue risk assessment based on the concept of energy

Fatigue risk in humans has few biomathematical models, and existing biomathematical models have many shortcomings. We developed a biomathematical model of fatigue risk based on the concept of energy to quantify human alertness from the perspective of energy and used alertness to characterise human psychological fatigue risk. The model allows mathematical modelling of activity processes that concern sleep intensity and quality and distinguishes between intrinsic exertion in the waking state and workload exertion in the workload state. This alertness and fatigue risk biomathematical model predicts changes in human alertness and fatigue risk indices at any point in the day. We applied numerical simulation and model analysis to five cases to validate the potential value of the alertness energy fatigue risk biomathematical model. Practitioner summary: To overcome the shortcomings of current biomathematical models that evaluate fatigue risk, this study developed a biomathematical model of fatigue risk based on the concept of energy to quantify human alertness from the perspective of energy and used alertness to characterise human fatigue risk. Abbreviations: S: The sleep homeostatic process; C: The circadian process; SAFTE: The sleep activity fatigue and task effectiveness model; FAID: The fatigue audit interdyne model; EEG: Electroencephalogram

Alertness Estimation Using Connection Parameters of the Brain Network

Alertness mechanism of unmanned monitoring vehicles to environment is important. Especially, the vigilance modeling of underground security robots has a particularly significance because the underground is a dangerous environment. However, there is no a mature methodology for the alertness computation. In this work, four parts of the alertness estimation are focused. First, an autonomous robot alertness mechanism framework is proposed by using the deep reinforcement learning model of the human alertness mechanism. Second, a fast K-T filtering algorithm is developed to eliminate the multiple noises of the electroencephalograph (EEG) signals by the blind source separation and the adjustable <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula> factor wavelet transform. Third, the description problem of the directed interaction stability of the cortical EEG signals is solved by the ensemble empirical mode decomposition and the directional transfer function. Fourth, the human alertness estimation is explored by using the support vector regression of the dynamically spatial-temporal brain network connection parameters. Experiments show that, the mean square error and the determination coefficient of the explored alertness estimation are respectively 0.115 and 0.8337. Compared with the scalp EEG alertness estimation, it has a better performance because the mean square error is decreased by 0.0684, and the determination coefficient is increased by 0.023.

Experimental Investigation of Task Performance and Human Vigilance in Different Noise Environments

Twelve healthy male college-age students were recruited to investigate the effects of different noise exposure conditions on complex task performance and vigilance. During each noise exposure, the Multi-Attribute Task Battery (MATB) with low, medium, and high mental workloads were conducted in the order designated by the Latin square method. Meanwhile, a psychomotor vigilance test (PVT) was used to evaluate human vigilance. Heart rate variability (HRV) signals were also collected while participants performed the tasks. The generalized additive mixed-effect model (GAMM) results showed that the increased mental workload had an inverted U-shaped effect on MATB task performance. Noise exposure had no significant impact on the overall performance of MATB tasks. However, when exposed to increased noise sharpness at low mental workloads, Tracking Task (TRA) performance significantly decreased, whereas the System Monitoring Task (SYS) performance was significantly improved. In addition, higher noise sound pressure level and sharpness would impair human vigilance, which was reflected in a lower mean sample entropy of HRV and worse performance on the PVT. The results indicated that noise control in the workplace should consider both sound pressure level and sharpness.

Global Emergency System Based on WPAN and LPWAN Hybrid Networks.

There are multiple methods of communication for the transmission of every type of alarm. In the case of emergency systems, they are usually controlled by private companies that work as bridges between the source and the receiver of an emergency. Furthermore, it is necessary to use an independent communication system for each building, requiring human vigilance, leading to an increase in infrastructure and service costs as well as response time. This paper proposes a hybrid network by combining both wireless personal access network (WPAN) and low power wide access network (LPWAN) communication for the complete development of a communication architecture oriented to an emergency system. The main aim of this work is to provide a global emergency system that is focused on fire detection but is also suitable for other critical events, with low energy consumption, a wide communication range covering up to 50 km, and a low cost of service and infrastructure. This proposal reduces the total energy consumption of the system with respect to typical fire detection systems.

Temporal complexity of EEG encodes human alertness

Objective. Automatic human alertness monitoring has recently become an important research topic with important applications in many areas such as the detection of drivers’ fatigue, monitoring of monotonous tasks that require a high level of alertness such as traffic control and nuclear power plant monitoring, and sleep staging. In this study, we propose that balanced dynamics of Electroencephalography (EEG) (so called EEG temporal complexity) is a potentially useful feature for identifying human alertness states. Recently, a new signal entropy measure, called range entropy (RangeEn), was proposed to overcome some limitations of two of the most widely used entropy measures, namely approximate entropy (ApEn) and Sample Entropy (SampEn), and showed its relevance for the study of time domain EEG complexity. In this paper, we investigated whether the RangeEn holds discriminating information associated with human alertness states, namely awake, drowsy, and sleep and compare its performance against those of SampEn and ApEn. Approach. We used EEG data from 60 healthy subjects of both sexes and different ages acquired during whole night sleeps. Using a 30 s sliding window, we computed the three entropy measures of EEG and performed statistical analyses to evaluate the ability of these entropy measures to discriminate among the different human alertness states. Main results. Although the three entropy measures contained useful information about human alertness, RangeEn showed a higher discriminative capability compared to ApEn and SampEn especially when using EEG within the beta frequency band. Significance. Our findings highlight the EEG temporal complexity evolution through the human alertness states. This relationship can potentially be exploited for the development of automatic human alertness monitoring systems and diagnostic tools for different neurological and sleep disorders, including insomnia.

Human Alertness Optimization with a Three-Process Dynamic Model

Circadian rhythm is an important biological process for humans as it modulates a wide range of physiological processes, including body temperature, sleep-wake cycle, and cognitive performance. As the most powerful external stimulus of circadian rhythm, light has been studied as a zeitgeber to regulate the circadian phase and sleep. This paper addresses the human alertness optimization problem, by optimizing light exposure and sleep schedules to relieve fatigue and cognitive impairment, in cases of night-shift workers and subjects with certain mission periods based on dynamics of the circadian rhythm system. A three-process hybrid dynamic model is used for simulating the circadian rhythm and predicting subjective alertness and sleepiness. Based on interindividual difference in sleep type and living habits, we propose a tunable sleep schedule in the alertness optimization problem, which allows the appropriate tuning of sleep and wake times based on sleep propensity. Variational calculus is applied to evaluate the impacts of light and sleep schedules on the alertness and a gradient descent algorithm is proposed to determine the optimal solutions to maximize the alertness level in various cases. Numerical simulation results demonstrate that the cognitive performance during certain periods can be significantly improved by optimizing the light input and tuning sleep/wake times compared to empirical data.

Effects of Daytime Electric Light Exposure on Human Alertness and Higher Cognitive Functions: A Systematic Review.

This paper reports the results of a systematic review conducted on articles examining the effects of daytime electric light exposure on alertness and higher cognitive functions. For this, we selected 59 quantitative research articles from 11 online databases. The review protocol was registered with PROSPERO (CRD42020157603). The results showed that both short-wavelength dominant light exposure and higher intensity white light exposure induced alertness. However, those influences depended on factors like the participants’ homeostatic sleep drive and the time of day the participants received the light exposure. The relationship between light exposure and higher cognitive functions was not as straightforward as the alerting effect. The optimal light property for higher cognitive functions was reported dependent on other factors, such as task complexity and properties of control light. Among the studies with short-wavelength dominant light exposure, ten studies (morning: 3; afternoon: 7) reported beneficial effects on simple task performances (reaction time), and four studies (morning: 3; afternoon: 1) on complex task performances. Four studies with higher intensity white light exposure (morning: 3; afternoon: 1) reported beneficial effects on simple task performance and nine studies (morning: 5; afternoon: 4) on complex task performance. Short-wavelength dominant light exposure with higher light intensity induced a beneficial effect on alertness and simple task performances. However, those effects did not hold for complex task performances. The results indicate the need for further studies to understand the influence of short-wavelength dominant light exposure with higher illuminance on alertness and higher cognitive functions.

Self-compassion: the influences on the university students’ life satisfaction during the COVID-19 outbreak

Purpose This study investigates the relationship between self-compassion and life satisfaction, and there is a significant statistical correlation between some dimensions of the self-compassion scale (family, self-kindness, common human feelings and mental alertness). Design/methodology/approach The researcher used the Self-Compassion scale prepared by Neff (2003) translated by the researchers, in a sample of 150 students in Egypt, and Multidimensional Student’s Life Satisfaction Scale, developed by Huebner et al. (1998) translated by the researchers. Findings The results of the study showed that self-compassion is high in university students. The study also showed a negative correlation with the dimension of psychological self-judgment and life satisfaction, as it indicated the possibility of predicting life satisfaction through the dimensions of self-compassion, except for the dimensions of isolation and autism, and excessive communication with the self. It also indicated that there are no differences between males and females as far as the variable of self-compassion, as well as the absence of differences between males and females as far as the variable of satisfaction with life is concerned. However, the family dimension showed a difference in favor of males. Originality/value The inclusion of extension programs to develop self-compassion for various segments of society in light of the continuing corona pandemic, and paying attention to religious counseling programs that support the use of spiritual values in self-strengthening which is reflected in the strengthening of psychological resilience and thus a sense of satisfaction with life.