Fatigue Conditions Research Articles

Monitoring fatigue state with heart rate-based and subjective methods during intensified training in recreational runners.

The purpose of this study was firstly to examine the sensitivity of heart rate (HR)-based and subjective monitoring markers to intensified endurance training; and secondly, to investigate the validity of these markers to distinguish individuals in different fatigue states. A total of 24 recreational runners performed a 3-week baseline period, a 2-week overload period, and a 1-week recovery period. Performance was assessed before and after each period with a 3000m running test. Recovery was monitored with daily orthostatic tests, nocturnal HR recordings, questionnaires, and exercise data. The participants were divided into subgroups (overreached/OR, n=8; responders/RESP, n=12) based on the changes in performance and subjective recovery. The responses to the second week of the overload period were compared between the subgroups. RESP improved their baseline 3000m time (p<0.001) after the overload period (-2.5±1.0%), and the change differed (p<0.001) from OR (0.6±1.2%). The changes in nocturnal HR (OR 3.2±3.1%; RESP -2.8±3.7%, p=0.002) and HR variability (OR -0.7±1.8%; RESP 2.1±1.6%, p=0.011) differed between the subgroups. In addition, the decrease in subjective readiness to train (p=0.009) and increase in soreness of the legs (p=0.04) were greater in OR compared to RESP. Nocturnal HR, readiness to train, and exercise-derived HR-running power index had ≥85% positive and negative predictive values in the discrimination between OR and RESP individuals. In conclusion, exercise tolerance can vary substantially in recreational runners. The results supported the usefulness of nocturnal HR and subjective recovery assessments in recognizing fatigue states.

Prevalence of work-related burnout and associated factors among police officers in central Gondar zone, Northwest Ethiopia, 2023.

Work-related burnout is a state of physical and psychological fatigue and exhaustion resulting from chronic workplace stress related to work. The police workforce is vulnerable to this psychosocial hazard, which affects service delivery by police workers. However, there is little evidence about the prevalence of work-related burnout and associated factors among police officers in Ethiopia. Therefore, this research investigated the prevalence and predictor variables of work-related burnout among police officers in central Gondar zone, Northwest Ethiopia, 2023. An institution-based cross-sectional study was carried out from April 12 to May 12, 2023. A sample of 633 police officers was recruited through multistage random sampling techniques. To measure work-related burnout, a standardized, self-administered Copenhagen Burnout Inventory was used. To enter the collected data, EpiData V 4.6 and to analyze SPSS V 26 were used. To examine the association between work-related burnout and its predictor variables, both bivariable (p < 0.2) and multivariable (<0.05) logistic regression analyses were performed, and statistical significance was established via multivariable logistic regression. The response rate in this study was 96.05% (n = 608). The majority, 452 (74.3%) of the police officers, were male; the median (IQR) age of participants was 28. In the past six months, 45.7% of the police officers had experienced work-related burnout (n = 278). Being female, having a high job demand, having a high level of organizational police stress, having a moderate level of operational police stress, having a high level of operational police stress, experiencing job dissatisfaction, and sleeping troubles were risk factors significantly related to the occurrence of work-related burnout among police officers. According to this study, a significant number of police officers suffer from burnout due to their work. Police officers' work-related burnout was found to be influenced by factors such as sex, job demands, job satisfaction, workplace stress, organizational police stress, and sleeping troubles. To address this problem, improving the handling of work pressure, developing a stress management program, finding joy at work by improving interpersonal relationships and working conditions, offering support and inspiration to female police officers, and ensuring sufficient and restful sleep are advised.

The Effects of Fatigue on Landing Performance in Young Female Soccer Players

Objectives. Jumping and landing constitute two movements that are used with a very high frequency in all sports and are two skills that have received a lot of attention in the literature because of their relationship with injury risk. The aim of this study is to analyze the following aspects: (a) to determine whether fatigue negatively affects landing technique after a jump, and (b) to test whether different metabolic and neuromuscular exercises have an effect on the landing technique. Materials and methods. The sample is composed of young female soccer players Under 14 (n = 29, 13.06 ± 1.27 years, 47.8 ± 2.6 kg; 143.2 ± 3.4 cm). Before and after two training protocols aimed at determining the state of fatigue (functional agility short-term fatigue protocol, and RSA protocol), landing technique was assessed using the Landing ErrorScoring System (LESS). Results. The LESS assessment for the pre-fatigue and post-functional agility short-term fatigue protocol conditions showed a value of 6.78 ± 0.81 and 8.74 ± 0.77 respectively (p &gt; 0.001, ES: 1.39). The LESS assessment for the post-RSA protocol condition was 8.52 ± 0.87; this score was statistically significantly higher than the pre-fatigue condition (p &gt; 0.001, ES: 1.24). Conclusions. Intensive exercise, both neuromuscular and metabolic, appears to have an effect on the landing technique of young female soccer players.

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.

Research on the fatigue level of underground mine truck drivers with integration of cardiovascular and brain features

The fatigue of miners is one of the primary factors influencing unsafe behaviors in mining. To accurately identify the fatigue status of miners, prevent coal mine accidents, and simulate the loading and unloading operations of underground mine truck drivers.Collecting electroencephalogram (EEG) and electrocardiogram (ECG) feature indicators of mine truck drivers during different work periods, using SPSS software to conduct correlation analysis on the collected fatigue feature indicators, and studying the changes in fatigue feature indicators before and after the operation of mine truck drivers. The results indicate that when the underground mine truck drivers' brainwave band entropy (β/ θ)exceeds the fatigue threshold of 60 or the HR_MEAN heart rate index is below 0.05uv, the drivers are in a state of severe fatigue. The fatigue levels of underground mine truck drivers vary during different work periods, with drivers at 13:00 experiencing the most severe fatigue. The study found that reducing the midday working hours for underground mine truck drivers can effectively decrease the occurrence of fatigue.

Effect of Testing Conditions on Low-Cycle Fatigue Durability of Pre-Strained S420M Steel Specimens.

S420M steel subjected to strain-controlled low-cycle fatigue does not exhibit a period of cyclic properties stabilization. The maximum stress on a cycle continuously drops until fracture. For this reason, it is difficult to plan experimental research for different types of control in such a way that their results can be considered comparable. The aim of this paper is to present and discuss the results of tests conducted in various conditions of low-cycle fatigue of S420M steel specimens, both undeformed and pre-strained. In both loading conditions, after initial deformation, a significant change in the cyclic properties of steel described by the parameters of the hysteresis loop was observed. Also, the fatigue life of the pre-strained specimens appeared to be different from unstrained specimens and was affected by the test loading conditions. The reduction in life under controlled stress conditions was attributed to the increase in the extent of plastic deformation and stress and the occurrence of creep.

Study of the Point Method for fretting fatigue life prediction

With the improvement and success of the Theory of Critical Distances (TCD) in notch fatigue problems, the TCD, especially the Point Method (PM), combined with multiaxial fatigue criteria, has been used over the last few years to predict the fretting fatigue life. However, little attention is paid to the effect of different damage mechanisms, especially stress distribution, between the two conditions on the application of the PM. This paper aims to select a suitable path for the PM, considering various stress distributions, for the fretting fatigue life prediction of complete contacts. A new method is developed to select the suitable path of the PM for fretting fatigue life prediction. To validate the analysis, corresponding tests were carried out using an improved proving ring-like rig in a Ti-6Al-4V alloy. Predicted lives on all paths were calculated using the PM combined with different multiaxial fatigue criteria, without incorporating wear effects, and compared with experimental lives using an error bar graph. Results indicate that when the fretting wear is not considered, the minimum predicted life path is more suitable for the PM than the perpendicular and maximum predicted life paths. This suitable path is compared to the path selection in the uniaxial symmetric V-notch fatigue condition. Analysis shows that the conventional path (the notch bisector) of the PM produces the maximum predicted life for the notch fatigue condition. The cause of this different path selection of the PM in the two fatigue conditions is assumed to be the effect of the asymmetric stress distribution and fretting wear damage in the fretting fatigue condition.

Experimental Study on Low-Cycle Fatigue Characteristics of Marine Structural Steel

This research focuses on the experimental investigation of the low-cycle fatigue characteristics of marine structural steel. The study aimed to explore the behavior of marine-grade steel under low-cycle fatigue conditions. The experimental parameters include the fatigue life of the material, crack propagation behavior, and a comprehensive analysis of mechanical properties associated with various loading conditions. Based on the experimental results, a low-cycle fatigue crack propagation rate model for marine structural steel plates was established using CTOD as a characterization parameter. The primary objective of this research is likely to enhance the durability and safety of maritime structures, providing valuable technical insights for the field of naval engineering.

Algorithm for drowsiness detection based on hybrid brain network parameter optimization

Drowsiness detection is a test designed to detect a person’s reaction ability and speed while in a state of fatigue. This type of drowsiness detection has many practical applications in areas like driver monitoring, transportation industry, and workplace safety. In this paper, a new machine learning drowsiness detection algorithm based on hybrid brain network feature extraction is proposed. First, the raw electroencephalogram signals are segmented into 30 s epochs, which are decomposed with wavelet packet transform into 7 layers to extract 30 s sleep characteristic subbands and the 7-th layer subbands. After that, 30 s subbands are divided into 5 s subbands with 50% overlap. At the same time, 30 s subbands are reconstructed by phase space reconstruction (PSR), whose parameters are optimized through energy valley optimizer. Then, based on mutual information and horizontal visual graph, a hybrid brain network is constructed with the 7-th layer subbands, 5 s subbands and PSR subbands, respectively. Finally, network features and time–frequency features are extracted and input into random forest classifier. The performance of the algorithm is evaluated through two tests: subject-independent test and subject-non-independent test. The results show that in Sleep-EDF dataset, accuracy, κ coefficient, recall, precision and F1-score obtained by the proposed algorithm can reach 94.19%, 88.39%, 95.37%, 92.53% and 93.93%, respectively. In Sleep-EDF Expanded dataset, accuracy, κ coefficient, recall, precision and F1-score can reach 93.65%, 87.65%, 94.53%, 92.11%, and 92.89%, respectively.

Evaluating the feasibility and acceptability of an adapted fencing intervention in breast cancer surgery post-operative care: the RIPOSTE pilot randomized trial.

Adapted physical activity programs have shown promising results in reducing the physical, social and psychological side effects associated with breast cancer, but the extent to which they can be effectively adopted, implemented and maintained is unclear. The aim of this study is to use the framework to guide the planning and evaluation of programs according to the 5 following keys: Reach, Effectiveness, Adoption, Implementation and Maintenance (RE-AIM) framework to evaluate a fencing program under the French acronym RIPOSTE (Reconstruction, Image de soi, Posture, Oncologie, Santé, Thérapie, Escrime) literally in English (Reconstruction, Self-Image, Posture, Oncology, Health, Therapy, Fencing). This program is an innovative intervention focused on improving the quality of life (QoL) of breast cancer surgery patients through fencing. A convergent mixed methods pilot study was conducted to preliminary evaluate the different RE-AIM dimension of the pilot program. Twenty-four participants who have just undergone surgery for invasive breast cancer were randomly allocated in two groups: one group started immediately after their inclusion (Early RIPOSTE group) and the other started 3 months following their inclusion (Delayed RIPOSTE group). Participants answered a questionnaire at inclusion and at the end of the program on QoL, shoulder functional capacity, fatigue, anxiety-depression and physical activity. RIPOSTE program was able to reach mainly young and dynamic participants, attracted by the originality of fencing and keen to improve their physical condition. Regarding effectiveness, our results suggest a trend to the improvement of QoL, shoulder functional capacity, fatigue and anxiety-depression state, even without any significant differences between the Early RIPOSTE group and the Delayed RIPOSTE group. The cooperation, exchanges and cohesion within the group greatly facilitated the adoption of the program, whereas interruptions during school vacations were the main barriers. The intervention was moderately well implemented and adherence to the protocol was suitable. RIPOSTE is an acceptable and effective program for involving breast cancer survivors in physical activity, that needs to be tested at a larger scale to investigate its effectiveness, but has the potential to be transferred and scaled up worldwide.

Intelligent learners distraction and drowsiness prediction through EEG signal and iris angel position with brain vision algorithm

Distraction and fatigue are serious issues in online learning, and they directly impact educational outcomes. To achieve excellent academic achievement, students need to focus on their studies without being distracted or fatigued. Learners frequently overlook crucial information, directions, and concepts while they are passive and sleepy. They tend to miss important content, instructions, and concepts. Iris Angle Position (IAP) and electroencephalography (EEG) were used in this model to identify the behaviour of learners. Specifically, a Deep Convolutional Neural Network (DCNN) is constructed to extract IAP in order to accurately capture the learner’s facial area. EEG signals are effectively handled and sorted using deep reinforcement learning (DRL). The learners’ facial landmarks are retrieved from a frame using the dlib toolbox. Only eye landmark points from face landmarks alone are focused on in order to determine the learner’s behaviour. When the learners EEG signals and Iris positions are monitored simultaneously, it’s helpful to identify the learner’s fatigue state (LFS) and the learner’s distraction state (LDS). The Brain Vision Algorithm (BVA) uses iris position and minimal facial landmarks, along with brain activity, to properly identify the learner’s level of distraction and exhaustion. When a student is detected as being preoccupied or sleepy, an alert goes off automatically, and the educator gets performance feedback. Iris position data and brain-computer interface-based EEG signal values are utilised to identify distraction and sleepiness. Comparative tests have demonstrated that this innovative method offers fast and high-accuracy student activity detection in virtual learning settings. Applying the suggested approach to different existing classifiers yields an F-Score of 91.92%, a recall of 93.87%, and a precision of 92.37% . The results showed that the detection rates for both distracted and sleepy phases were higher than those attained with other currently used techniques.

Experimental investigation of thermomechanical fatigue behavior in directionally solidified Ni-based superalloy under in-phase and out-of-phase conditions

The fatigue behavior of a directionally solidified (DS) Ni-based superalloy was investigated under in-phase (IP) and out-of-phase (OP) thermomechanical fatigue (TMF) conditions. Specimens were tested under strain control with a temperature range of 450–850 °C. In some tests, an optional 5 min out-of-phase dwell (OPD) time was introduced. In the case of IP TMF, the primary damage manifestation was predominantly intergranular cracks, whereas in the OP tests, the damage was mainly transgranular cracks. The fatigue life of IP TMF was found to be significantly shorter than that of OP TMF. This indicated that the intergranular cracks propagated faster than the transgranular cracks. The dwell time did not influence the dominant damage form; however, it led to an increase in the density of the microcracks. This increase resulted in a reduced lifetime, leading to lower stress amplitudes and higher plastic strain amplitudes compared with the continuous cycle tests. In addition, cycle hardening became apparent during the initial stages of cyclic loading. The microstructures and damage evolution were examined to provide insights into the changes in fatigue life. A model for predicting the fatigue life of DS Ni-based superalloy under given test conditions has been assessed. The proposed fracture mechanics model, which outlines the failure mechanism of directionally solidified Ni-based superalloy under TMF conditions, has proven to be effective in predicting fatigue life.

Constitutive model of an additively manufactured combustor material at high-temperature load conditions

ABSTRACT In this paper, the high-temperature constitutive behaviour of an additively manufactured ductile nickel-based superalloy is investigated and modelled, with application to thermomechanical fatigue, low-cycle fatigue and creep conditions at temperatures up to 800 ∘ C. Thermomechanical fatigue tests have been performed on smooth specimens in both in-phase and out-of-phase conditions at a temperature range of 100 − 800 ∘ C, and creep tests at 625 ∘ C, 700 ∘ C, 750 ∘ C and 800 ∘ C. Additionally, low-cycle fatigue tests at different strain ranges and load ratios have been performed at 700 ∘ C, and tensile tests have been performed at 600 ∘ C, 700 ∘ C and 800 ∘ C. A clear anisotropic mechanical response is obtained in the experiments, where the anisotropic effects are larger at high stress levels in creep loadings. To capture this behaviour, a rate-dependent strain based on a double-Norton model has been adopted in the model, by which the creep and mid-life response of the thermomechanical fatigue tests can be simulated with good accuracy.

The Mediating Role of Intrinsic Motivation in the Relationship Between Organizational Support and Quantitative Workload and Work-Related Fatigue

Increasingly tight job competition means that workers often ignore work-related fatigue conditions, which can negatively impact workers and organizations, resulting in decreased health and work effectiveness and even work accidents. In order to prevent this, proper work-related fatigue management is needed. This research examines the role of intrinsic motivation as a mediator in the relationship between organizational support and quantitative workload with work-related fatigue. This research is quantitative research with a survey method. The sampling technique used was stratified random sampling. The measuring instruments used are the Occupational Fatigue Exhaustion/Recovery Scale (OFER), the Quantitative Workload Inventory (QWI), the short version of the Survey of Perceived Organizational Support (SPOS), and the Situational Motivation Scale (SIMS). Data analysis used path analysis and bootstrapping in SmartPLS 3.0. The analysis results show no mediating role for intrinsic motivation in the relationship between organizational support and quantitative workload with work-related fatigue. A high quantitative workload triggers increased work-related fatigue, so it needs to be balanced with sufficient organizational support.

The influence of 3D-printed PLA coatings on pure and fretting fatigue properties of AM60 magnesium alloys under cyclic bending loads

A study was conducted to compare the pure fatigue and fretting fatigue properties of AM60 magnesium alloys, with and without 3D-printed PLA coatings. The PLA coating layers led to an increase in the fatigue lifetime in both pure and fretting conditions. They delayed the crack initiation time compared to uncoated samples, thereby increasing fatigue lifetime. Additionally, in the case of fretting fatigue, PLA coating caused the fretting pads to reach the magnesium alloy later, which also contributed to the longer lifetime of coated samples, compared to uncoated specimens. Using field emission scanning electron microscopy, all specimens exhibited the brittle fracture behavior, with the presence of both cleavage and quasi-cleavage marks. By the fractography, it was found that the number of cracks in coated samples decreased in both pure and fretting fatigue conditions. Remarkably, PLA coating during fretting fatigue resulted in a significant enhancement of the fretting fatigue lifetime, within 56%–2182 %.

Analysis of induced dynamic biceps EMG signal complexity using Markov transition networks.

Surface electromyography (sEMG) is a non-invasive technique to characterize muscle electrical activity. The analysis of sEMG signals under muscle fatigue play a crucial part in the branch of neurorehabilitation, sports medicine, biomechanics, and monitoring neuromuscular pathologies. In this work, a method to transform sEMG signals to complex networks under muscle fatigue conditions using Markov transition field (MTF) is proposed. The importance of normalization to a constant Maximum voluntary contraction (MVC) is also considered. For this, dynamic signals are recorded using two different experimental protocols one under constant load and another referenced to 50% MVC from Biceps brachii of 50 and 45 healthy subjects respectively. MTF is generated and network graph is constructed from preprocesses signals. Features such as average self-transition probability, average clustering coefficient and modularity are extracted. All the extracted features showed statistical significance for the recorded signals. It is found that during the transition from non-fatigue to fatigue, average clustering coefficient decreases while average self-transition probability and modularity increases. The results indicate higher degree of signal complexity during non-fatigue condition. Thus, the MTF approach may be used to indicate the complexity of sEMG signals. Although both datasets showed same trend in results, sEMG signals under 50% MVC exhibited higher separability for the features. The inter individual variations of the MTF features is found to be more for the signals recorded using constant load. The proposed study can be adopted to study the complex nature of muscles under various neuromuscular conditions.

Influence of toe flexor muscle fatigue on stiffness of the intrinsic foot muscles

BACKGROUND: Assessing intrinsic foot muscles (IFM) is important for understanding their role in loading movements. Additionally, knowledge of the impact of IFM following toe flexor muscle fatigue may aid the teaching of IFM exercises. OBJECTIVE: To examine the influence of toe flexor muscle fatigue on IFM stiffness using ultrasound shear-wave elastography. METHODS: This study included 19 college students. IFM stiffness at 10%, 50%, and 90% body weight was measured using ultrasound-based shear-wave elastography. IFM including the abductor hallucis (AbH), flexor hallucis brevis (FHB), flexor digitorum brevis (FDB), and quadratus plantae (QP) were assessed. The fatigue induction protocol comprised a series of toe flexions at a controlled pace of 40 beats per minute and an amplitude of 75% of the maximum toe flexor strength for a duration of 5 minutes. RESULTS: Muscle stiffness significantly increased with increasing load. Toe flexor muscle fatigue significantly increased the stiffness of the FDB. CONCLUSIONS: IFM stiffness significantly increased with increasing load, and the stiffness of FDB significantly increased in the toe flexor muscle fatigue condition at DLS and SLS loads. The findings of this study will contribute to the study and clinical setting of IFM exercises.

A Digital Twin for Assessing the Remaining Useful Life of Offshore Wind Turbine Structures

This paper delves into the application of digital twin monitoring techniques for enhancing offshore floating wind turbine performance, with a detailed case study that uses open-source digital twin software. We explore the practical implementation of digital twins and their efficacy in optimizing operations and predictive maintenance, focusing on controlling the real-time structural state of composite wind turbine structures and forecasting the remaining useful life by tracking the fatigue state in the structure. Our findings emphasize digital twins’ potential as a valuable tool for renewable energy, driving efficiency and sustainability in offshore floating wind installations. These aspects, along with the aforementioned simulations, whether in real-time or forecasted, reduce costly and unnecessary inspections and scheduled maintenance.

Skeletal muscle fiber type and TMS-induced muscle relaxation in unfatigued and fatigued knee-extensor muscles.

The force drop after transcranial magnetic stimulation (TMS) delivered to the motor cortex during voluntary muscle contractions could inform about muscle relaxation properties. Because of the physiological relation between skeletal muscle fiber-type distribution and size and muscle relaxation, TMS could be a noninvasive index of muscle relaxation in humans. By combining a noninvasive technique to record muscle relaxation in vivo (TMS) with the gold standard technique for muscle tissue sampling (muscle biopsy), we investigated the relation between TMS-induced muscle relaxation in unfatigued and fatigued states, and muscle fiber-type distribution and size. Sixteen participants (7F/9M) volunteered to participate. Maximal knee-extensor voluntary isometric contractions were performed with TMS before and after a 2-min sustained maximal voluntary isometric contraction. Vastus lateralis muscle tissue was obtained separately from the participants' dominant limb. Fiber type I distribution and relative cross-sectional area of fiber type I correlated with TMS-induced muscle relaxation at baseline (r = 0.67, adjusted P = 0.01; r = 0.74, adjusted P = 0.004, respectively) and normalized TMS-induced muscle relaxation as a percentage of baseline (r = 0.50, adjusted P = 0.049; r = 0.56, adjusted P = 0.031, respectively). The variance in the normalized peak relaxation rate at baseline (59.8%, P < 0.001) and in the fatigue resistance (23.0%, P = 0.035) were explained by the relative cross-sectional area of fiber type I to total fiber area. Fiber type I proportional area influences TMS-induced muscle relaxation, suggesting TMS as an alternative method to noninvasively inform about skeletal muscle relaxation properties.NEW & NOTEWORTHY Transcranial magnetic stimulation (TMS)-induced muscle relaxation reflects intrinsic muscle contractile properties by interrupting the drive from the central nervous system during voluntary muscle contractions. We showed that fiber type I proportional area influences the TMS-induced muscle relaxation, suggesting that TMS could be used for the noninvasive estimation of muscle relaxation in unfatigued and fatigued human muscles when the feasibility of more direct method to study relaxation properties (i.e., muscle biopsy) is restricted.

Compassion Fatigue Amongst Resident Doctors of a Medical College

Background: The healthcare sector demands tireless commitment and resident doctors go through intensive clinical training with long working hours and emotionally charged patient interactions. This might lead to emotional exhaustion, reduced empathy, and a sense of diminished personal accomplishment, all of which is a part of the complex psychological condition of compassion fatigue, which can profoundly impact the well-being of healthcare professionals. Compassion fatigue is a term given to the secondary stress suffered by those in helping professions who are working with those suffering from trauma.Objectives: (1) To assess the prevalence of compassion fatigue in resident doctors. (2) To find out the association between compassion fatigue and work-related factors among resident doctors.Methods: The present cross-sectional study was done among the doctors in the Tertiary Care Centre of district Meerut. Data was collected from 200 residents of different departments and medical specialities using a questionnaire consisting of professional quality of life scale along with information regarding sociodemographic and work-related factors.Result: A higher level of compassion satisfaction was seen in those who had more years of practice. Residents with excessive number of work hours and predominantly overnight shifts appear to be at higher risk of developing compassion fatigue related to higher burnout and secondary traumatic stress.Conclusion: The assessment of compassion fatigue among resident doctors highlights the impact of working conditions on their well-being. Addressing factors like long working hours, high patient loads, and lack of support from administration will help reduce compassion fatigue among the resident doctors.