Periods Of Workload Research Articles

Analysis of Influencing Factors on Participation Compliance, Slide Preparations Quality and Microscopic Reading Quality of Acid-Resistant Bacteria Slides at Ciamis Regency

Background & Objective: To find out the factors that influence participation compliance, slide preparations quality and microscopic reading quality in the External Quality Control program of Microscopic Cross Tests Acid Resistant Bacteria in Ciamis Regency in 2022-2023 Method: The research design is cross-sectional, population and total sampling of 27 respondents. Data analysis is Chi-Square with Fisher's Exact Test Result: Research data shows that the sig-p value of the period of employment variable for participation is 0.057, for the quality of slide preparations per quarter 0.695, 0.447, 0.550, 0.305, and the microscopic reading quality 0.036. The sig-p value of the training variable on participation is 0.226, on the quality of slide preparations per quarter 0.043, 0.388, 0.212, 0.219, and the microscopic reading quality 0.298. The sig-p value of the workload variable for participation is 0.204, for the quality of slide preparations per quarter 0.502, 0.091, 0.332, 0.502, and for the microscopic reading quality 0.050. The sig-p value of the microscope condition variable for participation is 0.005, for the quality of slide preparations per quarter 0.063, 0.106, 0.149, 0.323, and for the microscopic reading quality 0.036. The sig-p value of the incentive variable for participation is 0.001, for the quality of slide preparations per quarter 0.528, 0.302, 0.586, 0.189, for the microscopic reading quality of 0.013 Conclusion: there is a relationship between microscope conditions and incentive on participation compliance, there is a relationship between training on the slide preparations quality in the 4th quarter of 2022, there is a relationship between period of employment, workload, microscope conditions and incentive on microscopic reading quality

Energy efficient Security Driven Scheduling for Real-Time Tasks through DVS-enabled Fog Networks

The issue of task scheduling for a multi-core processor in Fog networks, with a focus on security and energy efficiency is of great importance in real-time systems. Currently, scheduling algorithms designed for cluster computing environments utilize dynamic voltage scaling (DVS) to decrease CPU power consumption, albeit at the expense of performance. This problem becomes more pronounced when a real-time task requires robust security, resulting in heavily overloaded nodes (CPUs or computing systems) in a cluster computing environment. To address such challenges, a solution called “Energy efficient Security Driven Scheduling of Real-Time Tasks using DVS-enabled Fog Networks (ESDS)” has been proposed. The primary goal of ESDS is to dynamically adjust CPU voltages or frequencies based on the workload conditions of nodes in Fog networks, thereby achieving optimal trade-offs between security, scheduling, and energy consumption for real-time tasks. By dynamically reducing voltage or frequency levels, ESDS conserves energy while still meeting deadlines for both running and new tasks, especially during periods of high system workload. Comprehensive experiments have been carried out to compare the ESDS algorithm with established baseline algorithms, including MEG, MELV, MEHV, and AEES. These experiments affirm the originality and effectiveness of the ESDS algorithm.

An outbreak of multi-drug-resistant Acinetobacter baumannii on a burns ICU and its control with multi-faceted containment measures

BackgroundPatients in burn centres are at high risk of acquiring multidrug-resistant pathogens due to reduced skin barrier and long hospital stay. MethodsWe report the investigation and control of an outbreak due to multidrug-resistant Acinetobacter baumannii in a burn centre. The 27 patients hospitalized in the centre during the outbreak were regularly screened and a total of 132 environmental samples were performed to identify a potential source. Fourier-transform infrared (FT-IR) spectroscopy and multilocus sequence typing (MLST) were applied to characterise the outbreak strain. ResultsBetween August and November 2022, the outbreak affected eight patients with eleven infections and three potentially related fatal outcomes. An interdisciplinary and multiprofessional outbreak team implemented a bundle strategy with repetitive admission stops, isolation precaution measures, patient screenings, enhanced cleaning and disinfection, and staff education. FT-IR spectroscopy suggested that the outbreak started from an index patient, who was repatriated one month before from a country with high prevalence of MDR A. baumannii. Environmental sampling did not identify a common source. Acquisition of the outbreak strain was associated with larger burn lesions ≥ 2a (per percent increase odds ratio (OR) 1.05 (0.99-1.12), P=0.09), and inversely associated with a higher nurse-to-patient ratio (per 0.1 increase OR 0.34, 95%CI 0.10-1.12, P=0.06). ConclusionsBurn patients with a large area of affected body surface, are at high risk for colonization and infection due to MDRO, particularly during periods of high workload. A multifaceted containment strategy can successfully control outbreaks due to MDR A. baumannii in a burn centre.

INTERFERENCE VS ENHANCEMENT : WORK-LIFE BALANCE DIMENSIONS ON JOB SATISFACTION AND TURNOVER INTENTION

The increase in jobs at software development companies has in-creased much faster than the average for other jobs. Intention to change jobs is one of the bad work-related outcomes for software development companies. Work-life balance has been found to reduce the intention in changing jobs. Individuals who have balanced work and life will experience less work overload and depression, and find it easier to carry out work and life roles. This research aims to determine the influence of work-life balance dimensions and job satisfaction on turnover intention. The research method used was descriptive and quantitative involving 61 respondents (saturated sample), and was conducted from December 2022 to April 2023. The sampling technique used was non-probability sampling with a saturated sample or census. Data processing and analysis techniques use PLS-SEM via SmartPLS 3.0 software. The results of the research produced several conclusions, namely two dimensions representing work-life balance that have a significant effect, namely personal life interference with work (PLIW) which is detrimental to job satisfaction, and work interference with personal life (WIPL) which has a positive effect on turnover intention. job satisfaction has a significant negative effect on employee turnover intentions. The step that companies need to take is to pay attention to work interference with personal life, especially related to fatigue after working during peak workload periods. Companies can provide facilities in the form of multivitamins to employees and carry out regular weekly sports activities to increase employee stamina.

Assessment of radio-activation using spectroscopy in medical linear accelerators.

In radiotherapy, when photon energy exceeding 8 MV is utilized, photoneutrons can activate the components within the gantry of the linear accelerator (linac). At the end of the linac's lifecycle, radiation workers are tasked with its dismantling and disposal, potentially exposing them to unintentional radiation. This study aims to identify and measure the radioisotopes generated by this activation through spectroscopy, and to evaluate the effective dose rate. We selected nine medical linacs, considering various factors such as manufacturer (Siemens, Varian, and Elekta), model, energy, period of operation, and workload. We identified the radionuclides in the linac head by employing an in situ high-purity germanium (HPGe) detector. Spectroscopy and dose-rate measurements were conducted post-shutdown. We also measured the dose rates at the beam-exit window following irradiation with 10 MV and 15 MV photon beams. As a result of the spectroscopy, we identified approximately 20 nuclides including those with half-lives of 100 days or longer, such as 54Mn, 60Co, 65Zn, 122Sb, and 198Au. The dose rate measurements after 10 MV irradiation decreased to the background level in 10 min. By contrast, on 15 MV irradiation, the dose rate was 628 nSv/h after 10 min and decreased to 268 nSv/h after 1.5 hours. It was confirmed that the difference in the level of radiation and the type of nuclide depends on the period of use, energy, and workload. However, the type of nuclide does not differ significantly between the linacs. It is necessary to propose appropriate guidelines for the safety of workers, and disposal/move-install should be planned while taking into consideration the equipment's energy usage rate.

Physiological Signals as Predictors of Mental Workload: Evaluating Single Classifier and Ensemble Learning Models

With a growing emphasis on cognitive processing in occupational tasks and the prevalence of wearable sensing devices, understanding and managing mental workload has broad implications for safety, efficiency, and well-being. This study aims to develop machine learning (ML) models for predicting mental workload using Heart Rate Variability (HRV) as a representation of the Autonomic Nervous System (ANS) physiological signals. A laboratory experiment, involving 34 participants, was conducted to collect datasets. All participants were measured during baseline, two cognitive tests, and recovery, which were further separated into binary classes (rest vs workload). A comprehensive evaluation was conducted on several ML algorithms, including both single (Support Vector Machine/SVM and Naïve Bayes) and ensemble learning (Gradient Boost and AdaBoost) classifiers and incorporating selected features and validation approaches. The findings indicate that most HRV features differ significantly during periods of mental workload compared to rest phases. The SVM classifier with knowledge domain selection and leave-one-out cross-validation technique is the best model (68.385). These findings highlight the potential to predict mental workload through interpretable features and individualized approaches even with a relatively simple model. The study contributes not only to the creation of a new dataset for specific populations (such as Indonesia) but also to the potential implications for maintaining human cognitive capabilities. It represents a further step toward the development of a mental workload recognition system, with the potential to improve decision-making where cognitive readiness is limited and human error is increased.

Lost in the middle – a pragmatic approach for ERP managers to prioritize known vulnerabilities by applying classification and regression trees (CART)

PurposeCyber risk has significantly increased over the past twenty years. In many organizations, data and operations are managed through a complex technology stack underpinned by an Enterprise Resource Planning (ERP) system such as systemanalyse programmentwicklung (SAP). The ERP environment by itself can be overwhelming for a typical ERP Manager, coupled with increasing cybersecurity issues that arise creating periods of intense time pressure, stress and workload, increasing risk to the organization. This paper aims to identify a pragmatic approach to prioritize vulnerabilities for the ERP Manager.Design/methodology/approachApplying attention-based theory, a pragmatic approach is developed to prioritize an organization’s response to the National Institute of Standards and Technology (NIST) National Vulnerability Database (NVD) vulnerabilities using a Classification and Regression Tree (CART).FindingsThe application of classification and regression tree (CART) to the National Institute of Standards and Technology’s National Vulnerability Database identifies prioritization unavailable within the NIST’s categorization.Practical implicationsThe ERP Manager is a role between technology, functionality, centralized control and organization data. Without CART, vulnerabilities are left to a reactive approach, subject to overwhelming situations due to intense time pressure, stress and workload.Originality/valueTo the best of the authors’ knowledge, this work is original and has not been published elsewhere, nor is it currently under consideration for publication elsewhere. CART has previously not been applied to the prioritizing cybersecurity vulnerabilities.

Using machine learning methods and EEG to discriminate aircraft pilot cognitive workload during flight

Pilots of aircraft face varying degrees of cognitive workload even during normal flight operations. Periods of low cognitive workload may be followed by periods of high cognitive workload and vice versa. During such changing demands, there exists potential for increased error on behalf of the pilots due to periods of boredom or excessive cognitive task demand. To further understand cognitive workload in aviation, the present study involved collection of electroencephalogram (EEG) data from ten (10) collegiate aviation students in a live-flight environment in a single-engine aircraft. Each pilot possessed a Federal Aviation Administration (FAA) commercial pilot certificate and either FAA class I or class II medical certificate. Each pilot flew a standardized flight profile representing an average instrument flight training sequence. For data analysis, we used four main sub-bands of the recorded EEG signals: delta, theta, alpha, and beta. Power spectral density (PSD) and log energy entropy of each sub-band across 20 electrodes were computed and subjected to two feature selection algorithms (recursive feature elimination (RFE) and lasso cross-validation (LassoCV), and a stacking ensemble machine learning algorithm composed of support vector machine, random forest, and logistic regression. Also, hyperparameter optimization and tenfold cross-validation were used to improve the model performance, reliability, and generalization. The feature selection step resulted in 15 features that can be considered an indicator of pilots' cognitive workload states. Then these features were applied to the stacking ensemble algorithm, and the highest results were achieved using the selected features by the RFE algorithm with an accuracy of 91.67% (± 0.11), a precision of 93.89% (± 0.09), recall of 91.67% (± 0.11), F-score of 91.22% (± 0.12), and the mean ROC-AUC of 0.93 (± 0.06). The achieved results indicated that the combination of PSD and log energy entropy, along with well-designed machine learning algorithms, suggest the potential for the use of EEG to discriminate periods of the low, medium, and high workload to augment aircraft system design, including flight automation features to improve aviation safety.

SG-APSIC1182: Sequential time workforce management

Objectives: Since 2018, the workload in the central sterilization services department (CSSD) has intensified as surgeries have increased. The extended operative time among complicated surgical cases has also led to shortages of resterilized surgical instruments. One factor influencing these shortages was inadequate CSSD staff during high workload periods. We developed a strategy to improve the availability of resterilized instruments. We sought to reduce wasted time and improve effectiveness of surgical instrument preparation by adopting a shift-work arrangement. We additionally sought to minimize unorganized instrumentation and surgical equipment loss. Methods: Team members investigated workload disproportion shift by shift. We devised a practical arrangement of staff for each work shift by dividing manpower in ratios based on workload. Results: The period from 10:00 a.m. to 7:00 p.m. was the period of most intense workload in the CSSD. However, 3 staff worked the morning shift and 2 staff worked the evening shift (4:00 p.m.– 2.00 a.m.). We reassigned 1 person to work from 8.00 a.m. to 4.00 p.m. and 2 persons for an extra shift from 10:30 a.m. to 6:30 p.m. After the manpower readjustment, surgical equipment damage and loss decreased from 57 to 26 losses per year from 2018 to 2021. In addition, work productivity increased from 85% to 115%. Worker satisfaction improved >70%. Conclusions: Internal inconsistency concerning instrumental preparation and improper instrument arrangement can affect surgery time. By addressing workload and shift distribution of labor, productivity notably improved, with higher satisfaction and a dramatic decrease in surgical equipment loss.

Skin Condition and Behavioral Factors in High-Performance Athletes Based on the Example of Professional Dance—An Explorative Pilot Project

The high work-related loads on the skin of dancers is the result of numerous factors. While initial studies have looked at the consequences of exposure, information on skin condition is still completely lacking. This study includes for the first time an analysis of the skin as well as the relevant skin care behaviour. Methods: A total of n = 35 professional dancers (PT) underwent skin analysis (transepidermal water loss, TEWL; moisture content and oil level) as part of a dermatological examination. This was done at different work load periods (phase of increased demands and resting phases, T1 and T0, respectively). Results: Acne (17.1%), herpes labialis (8.6%), and allergic rhinitis (14.3%) were among the most common pre-existing conditions. Low moisture contents and oil levels of the skin were found in selected localizations. TEWL index values were normal. There were no significant differences in measured values between T0 and T1. Subjects with skin lesions at rest showered significantly more often than their unaffected counterparts. Inflammation was particularly frequent after hair removal, especially in the intimate area (40.6%). Conclusions: Occupational exposures appear to be reflected in the results. However, studies with larger groups are needed to verify these results.

Efficacy of Aromatherapy at Relieving the Work-Related Stress of Nursing Staff from Various Hospital Departments during COVID-19.

This study aimed to evaluate the efficacy of aromatherapy in relieving the stress of nursing staff working in different departments during COVID-19. A total of 26 nursing staff from Taiwan were recruited for this study. Bergamot essential oil was diffused for over a four-week period in four different hospital departments. We assessed heart rate variability indicators, Nurse Stress Checklist, and Copenhagen Burnout Inventory before and after the intervention. The results of the analysis showed that during a high workload period, aromatherapy had no significant effect on regulating physical stress. Subjective measurements showed a significant impact on work concern and personal fatigue. Moreover, there were large differences among the four departments; the aromatherapy treatment had a weak effect on those with a heavy workload, whereas those with a lighter workload showed a stronger effect. Finally, this study provides practical results about aromatherapy stress reduction applied during the pandemic on first-line medical staff.

Hand Hygiene Compliance Decreases as Workload Increases

According to this study: Hand hygiene compliance decreased significantly in the ICU setting when the number of hand hygiene opportunities exceeded 30 per hour.Adequate staffing during higher workload periods is needed to ensure that health care providers maintain a high level of hand hygiene compliance.

Shape Matters: A Neglected Feature of Medication Safety : Why Regulating the Shape of Medication Containers Can Improve Medication Safety.

This paper aims to highlight how to reduce medication errors through the implementation of human factors science to the design features of medication containers. Despite efforts to employ automation for increased safety and decreased workload, medication administration in hospital wards is still heavily dependent on human operators (pharmacists, nurses, physicians, etc.). Improving this multi-step process requires its being studied and designed as an interface in a complex socio-technical system. Human factors engineering, also known as ergonomics, involves designing socio-technical systems to improve overall system performance, and reduces the risk of system, and in particular, operator, failures. The incorporation of human factors principles into the design of the work environment and tools that are in use during medication administration could improve this process. During periods of high workload, the cognitive effort necessary to work through a very demanding process may overwhelm even expert operators. In such conditions, the entire system should facilitate the human operator's high level of performance. Regarding medications, clinicians should be provided with as many perceptual cues as possible to facilitate medication identification. Neglecting the shape of the container as one of the features that differentiates between classes of medications is a lost opportunity to use a helpful characteristic, and medication administration failures that happen in the absence of such intentional design arise from "designer error" rather than "user error". Guidelines that define a container's shape for each class of medication would compel pharmaceutical manufacturers to be compatible and would eliminate the confusion that arises when a hospital changes the supplier of a given medication.

Factors Causing Work Stress Levels In Oil Palm Harvesting Workers At PT. Cipta Davia Mandiri In Kutai Timur District

Background: plantation activities in the form of harvesting and caring for oil palm require energy or labor or a heavy workload because at the time of these activities' workers need a lot of stamina or energy, especially the production department or harvester section. In connection with these stages, careful handling is needed to prevent work accident disorders including psychosocial disorders in the form of work stress. To anticipate the occurrence of work stress, workers need to be given an understanding of occupational safety and health (K3) through knowledge of factors that cause work stress.
 Research Methods: quantitative with the type of research that is analytic survey using cross sectional approach. The population in this study were workers harvesting oil palm PT. Cipta Davia Mandiri in East Kutai Regency, totaling 176 people. The sample is 122 respondents. Data analysis using the Chi-Square test.
 Results: there was an effect of age on the level of work stress in oil palm harvesting workers (p value: 0.000 <: 0.05). There is an effect of working period on the level of work stress on oil palm harvesting workers (p value: 0.000 <: 0.05). There is an effect of workload on the level of work stress on oil palm harvesting workers (p value: 0.013 <: 0.05).
 Conclusion: age, period of work and workload are factors that cause work stress levels. It is recommended that harvesters avoid work stress, need to create a decent work environment by fostering a family atmosphere and attitude and find solutions to solve problems.

Skin Health in Dance Focusing on Professional Dance and Latin American Formation Dance during Periods of Different Training Loads

Up to the present, there has been a lack of studies on the skin health of professional and recreational dancers. Dancers are at risk of skin diseases due to contact with allergenic or irritating substances and working in humid environments. The aim of the present study was, therefore, to examine skin health in two different dance styles and training periods. Methods: Physical dermatological examination of professional dancers (PD; n = 35) and Latin American formation dancers (LD; n = 79) after a 4-week period of recovery (T0) and a period of high training or work load (T1). Results: PD are significantly more frequently affected by skin dermatoses than LD (T0, p = 0.004) (frontal traction alopecia, hair loss, facial seborrhoea, xerosis cutis of the trunk and extremities, and facial folliculitis). The following significant differences between the sexes were observed in the LD: more folliculitis of the trunk in male subjects (T0 and T1, p = 0.009), more frequent xerosis cutis of the extremities (p < 0.001) and perioral dermatitis in female subjects (T1, p = 0.043). Subjects with skin lesions trained more frequently, performed more times per year, and had longer dance experience. Discussion: Based on the findings, preventive measures for skin protection (especially informing dancers about skin health) are necessary. At the same time, further studies on this topic are important.

Assessment of the nutritional profile through the 24-hour record in truckers in the central-southern Brazilian region: a prospective observational cross-sectional study

Introduction: Truck drivers are of great importance to the Brazilian economy. The exorbitant workload and long periods away from home are causes of the adoption of unhealthy eating habits, such as the intake of foods that are sources of lipids with high caloric value. Extensive travel contributes to a sedentary lifestyle. This causes health damage and comorbidities such as diabetes, obesity, hypertension, stress, and depression. Based on these considerations, the present study evaluates the nutritional profile of truck drivers. Objective: It was to evaluate the food quality of truck drivers in the Center-South Geoeconomic Region of the country, comparing the portions of macronutrients consumed with those recommended by the Brazilian Food Pyramid. Methods: Observational and cross-sectional study. The consumption of macronutrients by 100 truck drivers from the states of São Paulo, Minas Gerais, Mato Grosso do Sul and Goiás was qualitatively evaluated. The research used 24-hour food recalls, completed online, via Google Forms, between June and September 2020. Statistical analysis was obtained by calculating the Wilcoxon's non-parametric test to compare the medians of ingested portions and the ideas. Results: The Wilcoxon test identified significant differences between the number of servings consumed by truck drivers and the recommended ideal with regard to fruits, vegetables/vegetables, oils/fats, meats/eggs, sweets/sugars, milk, cheese and derivatives (p<0.0001). Only the portions of carbohydrates were in accordance with the nutritional recommendations, that is, six portions a day (ns). In the class of sugars and sweets, consumption four times higher than recommended was observed. In the meat and eggs category, consumption was double the ideal. In oils and fats, triple the recommended value. The consumption of milk and dairy products is three times less than ideal, such as vegetables. Finally, the average value of fruit portions eaten by truck drivers was zero, while the recommended value is three. Conclusion: Among the food groups analyzed, carbohydrates were the only group in which consumption was adequate. There was a significant excess of sweets and fats intake by truck drivers, when compared to the ideal amount indicated by the food pyramid. The intake of milk and dairy products, vegetables and legumes was deficient, three times lower than recommended. Fruits counted as a median intake value of zero servings.

Mental preparedness for prolonged periods of high workload – What did we learn from the covid-19 pandemic?

Mental preparedness for prolonged periods of high workload – What did we learn from the covid-19 pandemic?

Various Workload Models and the Preseason Are Associated With Injuries in Professional Female Cyclists.

To determine if workload and seasonal periods (preseason vs in season) are associated with the incidence of injuries and illnesses in female professional cyclists. Session rating of perceived exertion was used to quantify internal workload and was collected from 15 professional female cyclists, from 33 athlete seasons. One week (acute) workload, 4 weeks (chronic) workload, and 3 acute:chronic workload models were analyzed. Two workload models are based on moving averages of the ratios, the acute:chronic workload ratio (ACWR), and the ACWR uncoupled (ACWRuncoup). The difference between both is the chronic load; in ACWR, the acute load is part of the chronic load, and in ACWRuncoup, the acute and chronic load are uncoupled. The third workload model is based on exponentially weighted moving averages of the ratios. In addition, the athlete season is divided into the preseason and in season. Generalized estimating equations analysis was used to assess the associations between the workload ratios and the occurrence of injuries and illnesses. High values of acute workload (P = .048), ACWR (P = .02), ACWRuncoup (P = .02), exponentially weighted moving averages of the ratios (P = .01), and the in season (P = .0001) are significantly associated with the occurrence of injury. No significant associations were found between the workload models, the seasonal periods, and the occurrence of illnesses. These findings suggest the importance of monitoring workload and workload ratios in female professional cyclists to lower the risk of injuries and therefore improve their performances. Furthermore, these results indicate that, in the preseason, additional stressors occur, which could lead to an increased risk of injuries.

Objective Assessments of Mental Fatigue During a Continuous Long-Term Stress Condition.

Prolonged periods of cognitive workload will cause mental fatigue, but objective, quantitative, and sensitive measurements that reflect long-term, stress-induced mental fatigue have yet to be elucidated. This study aims to apply a potential marker of Rényi entropy to investigate the mental fatigue changes in a long-term, high-level stress condition and compare three different instruments for assessment of mental fatigue: EEG, the oddball task, and self-scoring. We recruited nine individuals who participated in a 5-day intellectually challenging competition. The participants were assessed for mental fatigue each day of the competition using prefrontal cortex electroencephalogram (EEG). Reaction time in an oddball task and self-rated scoring were used comparatively to evaluate the performance of the EEG. Repeated measures ANOVA was utilized to analyze the differences among score, reaction time, and wavelet Rényi entropy. The results demonstrated that both wavelet Rényi entropy extracted from EEG and self-rated scoring revealed significant increases in mental fatigue during the 5 days of competition (P < 0.001). The reaction time of the oddball task did not show significant changes during the five-day competition (P = 0.066). Moreover, the wavelet Rényi entropy analysis of EEG showed greater sensitivity than the self-rated scoring and reaction time of the oddball task for measuring mental fatigue changes. In conclusion, this study shows that mental fatigue accumulates during long-term, high-level stress situations. The study also indicates that EEG wavelet Rényi entropy is an efficient metric to reflect the change of mental fatigue under a long-term stress condition and that EEG is a better method to assess long-term mental fatigue.

Psychological and Physiological Changes in Response to the Cumulative Demands of a Women's Division I Collegiate Soccer Season.

McFadden, BA, Walker, AJ, Bozzini, BN, Hofacker, M, Russell, M, and Arent, SM. Psychological and physiological changes in response to the cumulative demands of a women's division I collegiate soccer season. J Strength Cond Res 36(5): 1373-1382, 2022-This study sought to determine the effects of a women's collegiate soccer season on psychological markers, biomarkers, sleep, and performance. Athletes participated in maximal countermovement vertical jump height (CMJ) assessments and biomarker monitoring in conjunction with subjective measures of psychological wellness and sleep questionnaires before preseason (S1) and every 4 weeks following (S2, S3, and S4). Training was monitored during practices and games using global positioning satellite systems and heart rate technology. Total training load was highest from S1 to S2, decreased from S2 to S3 (effect size [ES] = -2.5; p < 0.001), and remained stable from S3 to S4. CMJ declined at S2 (ES1-2 = -0.51; p = 0.001) and returned to baseline at S3. Increases from S1 to S2 were seen for creatine kinase (ES1-2 = 1.74), free testosterone (ES1-2 = 1.27), total testosterone (ES1-2 = 3.5), and free cortisol (ES1-2 = 0.88) (p < 0.03) before returning to baseline by S3 and S4 (free cortisol). Total cortisol was elevated throughout the season before declining at S4 (ES1-4 = -0.41; p = 0.03). Iron declined from S1 to S2 (ES1-2 = -0.73; p = 0.01) and returned to baseline values at S4, whereas growth hormone declined at S2 (ES1-2 = -0.50; p = 0.01) and remained depressed. Interleukin-6 increased at S4 (ES1-4 = 0.71; p = 0.02). Total training distress decreased from S1 to S2 (ES1-2 = -0.38; p = 0.02), returned to baseline by S3, and increased by S4 (ES1-4 = 0.57; p = 0.01). No changes were observed in markers of sleep (p > 0.05). Biomarkers showed notable changes after the highest workload period (S1-S2), which coincided with CMJ decrements. Biomarker perturbations preceded declines in subjective psychological wellness (S4) which occurred in the latter half of the season, indicating an accumulation of fatigue as the season progressed.