Mental Fatigue Research Articles

Labor fatigue and work organization in a food factory, Aragua-Venezuela, 2023

The objective was to evaluate work fatigue and work organization in a food factory, in the state of Aragua, 2023. Research with a quantitative, field, descriptive, cross-sectional and correlational scope approach. The population was 135 workers and the sample was 101 workers, obtained by snowball sampling. The Yoshitake questionnaire (1978) modified by INSAT 1987 was applied. The statistical programs IBM SPSS ® Statistics Version 25 and EPIDAT were used. The sample was characterized using descriptive statistics and correlated by applying the chi-square and p-value tests. Results: The average age was 42.59 years, predominantly female; 44.6% single; 52.5% live with their partner.; 51.5% have secondary education; the family burden is less than or equal to three members in 61.4%; working workforce 80.2% all under rotating shift schemes; 63.4% have a length of service greater than 16 years; the travel time to the workplace is less than 30 minutes in 56.4%; 62.38% presented fatigue, in this group, 84.13% with general symptoms of fatigue, followed by 9.52% with mental fatigue, and 6.35% physical fatigue. It is concluded that 62.4% present mixed type work fatigue. Women, workers, those who live far away and those who worked shifts are more affected. There are no statistically significant differences between socio-occupational characteristics, shift work and the presence of fatigue.

A Cross-Sectional Study to Analyze the Physical and Cognitive Fatigue Due to Sleep Disruption Among Shift Workers in Tamilnadu

The objective of this research is to analyse the extent and manner of the kind of fatigue among shift workers in Tamil Nadu, India. As for shift workers, they often have disturbed night’s sleep. Shift work is distinguished by its irregular and unique work hours, unlike the regular day-time Schedule. It is combined with circadian alteration, which affects most of the bodily activities. They have diverse sorts of health problems, such as physical and mental fatigue. A Cross-sectional Analysis was done among airport workers. 200 participants were randomly selected for the study aged 35-45 years and conducted for a duration of 6 months in the Airport, Tamilnadu. Sleep quality and cognition were assessed using a validated questionnaire. The muscle fatigue was evaluated using Mosso’s ergograph. R-statistical Software (version 4.0.2) was used for Data Analysis. The Primary analyses of data set’s normality were done by Kolmogorov - Smirnov Z test. Significant negative correlation exists between global PSQI score and both cognition score (r= -0.315, P<0.001) and Work done by Mosso (r= -0.405, P<0.001) There is also negative correlation exists between work done and the cognition score (r= - 0.565, P<0.001) which is statistically significant. Decreased Sleep Quality, more fatigue and lowering of cognition levels not only affects physical health but also the quality of life. It has been noted that sleep disturbance leads to physical and mental exhaustion among Tamil Nadu shift workers. The outcomes underscore the need for targeted interventions to improve sleep-related behaviours as well as the treatment of fatigue in this population. Reducing the disturbances of shift work effects on produce, growth as well as health may be authorized by way of implementing organized work shifts and also promoting sleep promotion.

Examining the effect of maintenance work on employees’ physical and mental health, as well as their overall well-being, in industrial settings

This study examines the impact of maintenance work on the physical, mental health, and overall well-being (PMHOW) of employees in some industry types in South Eastern Nigeria. The research aims to enhance occupational health standards and support interventions for industrial maintenance workers. It identifies the stressors that maintenance workers face (physical work demands, high-pressure work environment, shift work and irregular work hours, lack of recognition and support, exposure to hazardous conditions, job complexity and technical challenges, and; monotony and repetitive tasks), these stressors affect employees’ health and well-being through musculoskeletal disorders, mental fatigue, increased risk of accidents, stress, anxiety, and burnout to mention but a few, it proposes strategies for mitigating them which include ergonomic practices, realistic workloads, supportive work culture, adequate staffing etc. Employee Satisfaction Survey was conducted across targeted industries. Based on survey results, employees' perceptions of variances in work characteristics reveal a mix of stable and fluctuating trends. This information helped identify which work characteristics were consistently experienced and which ones vary significantly among employees. Euclidean Distance assessment carried out also aided in identifying areas of intervention by focusing on specific groups of related work characteristics to enhance the work environment and promote better health outcomes. To enhance the mental and physical well-being of maintenance workers, organizations should implement comprehensive strategies that are tailored to the unique stressors and challenges of their work. This approach will not only boost job satisfaction but also contribute to a more efficient and healthier workforce.

Does the Effect of Mental Fatigue Created by Motor Imagery on Upper Extremity Functions Change with Diaphragmatic Breathing Exercises? A Randomized, Controlled, Single-Blinded Trial.

Background and Objectives: This study focused on the impact of mental fatigue induced by motor imagery on upper limb function, an area with limited research compared to lower limb performance. It aimed to explore how diaphragmatic breathing exercises influence these effects. Materials and Methods: This study included 30 participants, and Group 1 participated in 12 sessions of diaphragmatic breathing exercises under the supervision of a physiotherapist; Group 2 did not receive any intervention. For all the participants, mental fatigue was induced with motor imagery before and after the intervention, and evaluations were performed before and after mental fatigue. Upper extremity functions were evaluated using isometric elbow flexion strength, hand grip strength, upper extremity reaction time and endurance, finger reaction time, the nine-hole peg test, shoulder position sense, light touch-pressure threshold, and two-point discrimination. Results: The study results showed that after mental fatigue, there was a decrease in isometric elbow flexion strength, nondominant hand grip strength, and nondominant upper extremity endurance, and an increase in nondominant tactile sensation (p < 0.05). No changes were found in two-point discrimination, nine-hole peg test time, and position sense on either side (p > 0.05). The effect of mental fatigue on isometric elbow flexion strength and nondominant grip strength showed significant improvement following diaphragmatic breathing exercises (p < 0.05). Conclusions: This study found that mental fatigue from motor imagery can impact elbow flexion, hand grip strength, upper extremity endurance, and tactile sensitivity. Breathing exercises may help improve strength parameters affected by mental fatigue. It is crucial to consider these effects on upper extremity functions in rehabilitation programs.

Boosting arousal and cognitive performance through alternating posture: Insights from a multi-method laboratory study.

This study investigated the role of arousal and effort costs in the cognitive benefits of alternating between sitting and standing postures using a sit-stand desk, while measuring executive functions, self-reports, physiology, and neural activity in a 2-h laboratory session aimed to induce mental fatigue. Two sessions were conducted with a one-week gap, during which participants alternated between sitting and standing postures each 20-min block in one session and remained seated in the other. In each block, inhibition, switching, and updating were assessed. We examined effects of time-on-task, acute (local) effects of standing versus sitting posture, and cumulative (global) effects of a standing posture that generalize to the subsequent block in which participants sit. Results (N = 43) confirmed that time-on-task increased mental fatigue and decreased arousal. Standing (versus sitting) led to acute increases in arousal levels, including self-reports, alpha oscillations, and cardiac responses. Standing also decreased physiological and perceived effort costs. Standing enhanced processing speed in the flanker task, attributable to shortened nondecision time and speeded evidence accumulation processes. No significant effects were observed on higher-level executive functions. Alternating postures also increased heart rate variability cumulatively over time. Exploratory mediation analyses indicated that the positive impact of acute posture on enhanced drift rate was mediated by self-reported arousal, whereas decreased nondecision time was mediated by reductions in alpha power. In conclusion, alternating between sitting and standing postures can enhance arousal, decrease effort costs, and improve specific cognitive and physiological outcomes.

Portrait of mental health identified by people with the post-covid syndrome.

This study aimed to produce a patient-centered understanding of mental health symptoms of people with the post-COVID-19 syndrome (PCS). A cross-sectional analysis of 414 participants in a longitudinal study was carried out involving people who self-identified as having symptoms of PCS. People were asked to name their most frequent and most bothersome mental health symptoms affected by PCS using the structure of the Patient Generated Index (PGI). The text threads from the PGI were grouped into topics using BERTopic analysis. 20 topics were identified from 818 text threads referring to PCS mental health symptoms. 35% of threads were identified as relating to anxiety, discussed in terms of five topics: generalized/social anxiety, fear/worry, post-traumatic stress, panic, and nervous. 29% of threads were identified as relating to low mood, represented by five topics: depression, discouragement, emotional distress, sadness, and loneliness. A cognitive domain (22% of threads) was covered by four topics referring to concentration, memory, brain fog, and mental fatigue. Topics related to frustration, anger, irritability. and mood swings (7%) were considered as one domain and there were separate topics related to motivation, insomnia, and isolation. This novel method of digital transformation of unstructured text data uncovered different ways in which people think about classical mental health domains. This information could be used to evaluate whether existing measures cover the content identified by people with PCS, to initiate a clinical conversation, or to justify the development of a new measure of the mental health impact of PCS.

Factors influencing fatigue, mental workload and burnout among Chinese health care workers during public emergencies: an online cross-sectional study

ObjectivesThe purpose of this study was to investigate fatigue, mental workload, and burnout among health care workers (HCWs) and explore the possible underlying factors.Materials and methodsAn online cross-sectional survey design was used to collect data from HCWs in Chongqing, China. The online survey included the Fatigue Severity Scale, NASA Task Load Index, and Chinese version of the Maslach Burnout Inventory-General Survey to assess fatigue, mental workload, and burnout, respectively, and was conducted from February 1 to March 1, 2023.ResultsIn this study, the incidence of fatigue and burnout among HCWs was 76.40% and 89.14%, respectively, and the incidence of moderate to intolerable mental workloads was 90.26%. Work–family conflict, current symptoms, number of days of COVID-19 positivity, mental workload, burnout and reduced personal accomplishment were significantly associated with fatigue. Mental workload was affected by fatigue and reduced personal accomplishment. Furthermore, burnout was influenced by marital status and fatigue. Moreover, there was a correlation among mental workload, fatigue, and burnout.ConclusionsFatigue, mental workload and burnout had a high incidence and were influenced by multiple factors during COVID-19 public emergencies in China.

Long-Term Epidural Patching Outcomes and Predictors of Benefit in Patients With Suspected CSF Leak Nonconforming to ICHD-3 Criteria.

Spinal CSF leaks lead to spontaneous intracranial hypotension (SIH). While International Classification of Headache Disorders, Third Edition (ICHD-3) criteria necessitate imaging confirmation or low opening pressure (OP) for SIH diagnosis, their sensitivity may be limited. We offered epidural blood patches (EBPs) to patients with symptoms suggestive of SIH, with and without a documented low OP or confirmed leak on imaging. This study evaluates the efficacy of this strategy. We conducted a prospective cohort study with a nested case-control design including all patients who presented to a tertiary headache clinic with clinical symptoms of SIH who completed study measures both before and after receiving an EBP between August 2016 and November 2018. The mean duration of symptoms was 8.7 ± 8.1 years. Of 85 patients assessed, 69 did not meet ICHD-3 criteria for SIH. At an average of 521 days after the initial EBP, this ICHD-3-negative subgroup experienced significant improvements in Patient-Reported Outcomes Measurement Information System (PROMIS) Global Physical Health score of +3.3 (95% CI 1.5-5.1), PROMIS Global Mental Health score of +1.8 (95% CI 0.0-3.5), Headache Impact Test (HIT)-6 head pain score of -3.8 (95% CI -5.7 to -1.8), Neck Disability Index of -4.8 (95% CI -9.0 to -0.6) and PROMIS Fatigue of -2.3 (95% CI -4.1 to -0.6). Fifty-four percent of ICHD-3-negative patients achieved clinically meaningful improvements in PROMIS Global Physical Health and 45% in HIT-6 scores. Pain relief following lying flat prior to treatment was strongly associated with sustained clinically meaningful improvement in global physical health at an average of 521 days (odds ratio 1.39, 95% CI 1.1-1.79; p < 0.003). ICHD-3-positive patients showed high rates of response and previously unreported, treatable levels of fatigue and cognitive deficits. Patients who did not conform to the ICHD-3 criteria for SIH showed moderate rates of sustained, clinically meaningful improvements in global physical health, global mental health, neck pain, fatigue, and head pain after EBP therapy. Pre-treatment improvement in head pain when flat was associated with later, sustained improvement after EBP therapy among patients who did not meet the ICHD-3 criteria. This study provides Class IV evidence that epidural blood patch is an effective treatment of suspected CSF leak not conforming to ICHD-3 criteria for SIH.

Machine learning based severity classification of obstructive sleep apnea patients using awake EEG

Obstructive sleep apnea (OSA) is one of the most widespread breathing-based sleep disorders. Previous studies reported daytime sleepiness, mental fatigue, and cognitive decline in patients with OSA. The diagnosis of OSA is done with laborious overnight polysomnography (PSG) recording. This study aims to classify the severity of OSA patients according to the Apnea-Hypopnea Index (AHI) into mild and moderate to-serve groups (AHI ≥ 15) without using recorded signals during sleep, non-PSG signals and investigate the relevant features. For this purpose, 25 OSA patients participated in 3-minute eyes closed resting state EEG session on the following morning of overnight PSG recording. Time, spectral domain, and nonlinear features were extracted from the delta, theta, and alpha subbands’ of EEG signals. Several machine learning algorithms were used to classify patients’ severity. To investigate optimal feature combinations features were grouped according to their types (Time domain/spectral domain and nonlinear), their electrodes (frontal/central/parietal/occipital), and their subbands (delta/theta/alpha). Also, the Relief method was applied to select the most relevant features. A 5-fold cross validation method was used to generalize the model behaviour. Optimal feature combinations were selected according to classifiers' performances that were evaluated by accuracy, sensitivity, specificity, and area under curve (AUC) parameters when feature sets were used as input. The 15 selected features by the Relief method showed the best performances in the K-Nearest Neighbours (K = 5) classifier [accuracy: 93.33 % ± 5.27 %; sensitivity: 92.30 % ± 4.97 %; specificity: 94.14 % ± 4.24 %; AUC:0.98]. The findings establish that awake resting state EEG records might be used as a faster tool to use OSA severity level.

Relationship between physical fatigue and mental fatigue based on multimodal measurement under different load levels

Based on multimodal measurement methods of NASA task load index (NASA-TLX), task performance, surface electromyography (sEMG), heart rate (HR), and functional near-infrared spectroscopy (fNIRS), this study conducted experimental measurements and analyses under 16 different load levels of physical fatigue and mental fatigue combination conditions. This study observed the interaction between physical fatigue and mental fatigue at different levels, and at the subjective level, the effect of physical fatigue on mental fatigue was greater than that of mental fatigue on physical fatigue. Secondly, the results of fNIRS analysis showed that the premotor cortex is affected by physical fatigue, and the dorsolateral prefrontal cortex is affected by mental fatigue. Finally, this study constructed a fatigue classification model with an accuracy of 95.3%, which takes multimodal physiological data as input and 16 fatigue states as output. The research results will provide a basis for fatigue analysis, evaluation, and improvement in complex working situations.

Mental fatigue recognition study based on 1D convolutional neural network and short-term ECG signals.

Mental fatigue has become a non-negligible health problem in modern life, as well as one of the important causes of social transportation, production and life accidents. Fatigue detection based on traditional machine learning requires manual and tedious feature extraction and feature selection engineering, which is inefficient, poor in real-time, and the recognition accuracy needs to be improved. In order to recognize daily mental fatigue level more accurately and in real time, this paper proposes a mental fatigue recognition model based on 1D Convolutional Neural Network (1D-CNN), which inputs 1D raw ECG sequences of 5s duration into the model, and can directly output the predicted fatigue level labels. The fatigue dataset was constructed by collecting the ECG signals of 22 subjects at three time periods: 9:00-11:00 a.m., 14:00-16:00 p.m., and 19:00-21:00 p.m., and then inputted into the 19-layer 1D-CNN model constructed in the present study for the classification of mental fatigue in three grades. The results showed that the model was able to recognize the fatigue levels effectively, and its accuracy, precision, recall, and F1 score reached 98.44%, 98.47%, 98.41%, and 98.44%, respectively. This study further improves the accuracy and real-time performance of recognizing multi-level mental fatigue based on electrocardiography, and provides theoretical support for real-time fatigue monitoring in daily life.

Mental Fatigue in Sports: Causes, Effects, and Coping Strategies – A Review Study

Mental Fatigue in Sports: Causes, Effects, and Coping Strategies – A Review Study

CP-01. FATIGUE IN PATIENTS WITH HYPOTHALAMIC SYNDROME – A CROSS-SECTIONAL ANALYSIS IN THE GERMAN CHILDHOOD-ONSET CRANIOPHARYNGIOMA COHORT

Abstract BACKGROUND Patients with tumors of the sellar region are at risk of developing hypothalamic syndrome. Survivors experience fatigue and excessive daytime sleepiness even years after tumor treatment. The aim of this cross-sectional study was to determine the severity of fatigue in patients with and without hypothalamic syndrome. METHODS Patients diagnosed with CP or pilocytic astrocytoma were recruited from the KRANIOPHARYNGEOM 2000/2007/Registry 2019 studies and included in this analysis. Eligibility criteria were regular participation in outpatient after-care, one completed Multidimensional Fatigue Inventory-20 (MFI-20) questionnaire and complete medical records on criteria for hypothalamic syndrome. With univariable and multivariable linear regression, the relation of hypothalamic syndrome and levels of fatigue symptoms (MFI-20 sum score) were assessed. MFI-20 scores were compared to sex- and age-matched reference values from a German normative population using paired t-test. RESULTS Data on 46 patients, with a median age of 20 years, was available for this analysis of which 28 (61%) patients presented with hypothalamic syndrome. After adjustment for age and sex, patients with hypothalamic syndrome reported higher scores in the physical (= 3.61 [95% CI: 1.38–5.85]), mental (= 2.80 [95% CI: 0.28–5.32]) and sum MFI-20 (= 12.02 [95% CI: 2.93–21.10]) domain than patients without hypothalamic syndrome. Compared to reference values from a general German population, all patients reported higher mean scores in each fatigue domain. Regardless of the level of daytime sleepiness in patients with hypothalamic syndrome, the reported fatigue scores were high. Daytime sleepiness did not correlate with fatigue. CONCLUSIONS Fatigue symptoms are present in patients with CP. However, patients with hypothalamic syndrome are more affected in mental, physical and overall fatigue. It is crucial in clinical practice, to distinguish between sleep disorders and fatigue and to target patients with hypothalamic syndrome.

Fatigued or bored? Investigating the effect of different types of mental fatigue on 3 km running performance

Mental fatigue has been highly cited as having a negative impact on endurance performance. Few, however, have investigated whether different types of mental fatigue, namely active and passive fatigue, might affect endurance performance differently. This study used a repeated-measures design where 11 participants completed a 3 km run after three 32-min conditions: an actively fatiguing task (Task-load Dual-back; TloadDback); a passively fatiguing task (Mackworth Clock); and a control task (Documentary). Subjective ratings and performance on a second task (Flanker task) were taken before and after the 32-min tasks, while ratings of perceived effort, motivation and workload were taken during the 3 km run. Results showed that both fatigue conditions were mentally fatiguing, with the TloadDback rated as more demanding and the Mackworth Clock more boring and less motivating. Performance on subsequent tasks showed different effects: the TloadDback condition had the slowest responses on the post-test Flanker task, while the Mackworth Clock condition had the slowest completion time on the 3 km run, though this difference in completion times was non-significant. These results suggest that different cognitive tasks lead to different types of mental fatigue, which can lead to different outcomes on subsequent cognitive tasks but non-significant differences on subsequent physical tasks. This study highlights that to understand the influence of mental fatigue on physical performance, it is important to understand the cognitive tasks used and how different cognitive and physical tasks interact. Future work should examine whether performance outcomes in other areas commonly affected by mental fatigue, like technical and tactical sporting skills, are affected differently by active and passive fatigue.

The effect of transcranial electrical stimulation on the relief of mental fatigue.

The presence of mental fatigue seriously affects daily life and working conditions. Non-invasive transcranial electrical stimulation has become an increasingly popular tool for relieving mental fatigue. We investigated whether transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS) could be used to alleviate the state of mental fatigue in a population of healthy young adults and compared their effects. We recruited 10 participants for a blank control, repeated measures study. Each participant received 15 min of anodal tDCS, α-tACS, and blank stimulation. Participants were required to fill in the scale, perform the test task and collect ECG signals in the baseline, fatigue and post-stimulus states. We then assessed participants' subjective fatigue scale scores, test task accuracy and HRV characteristics of ECG signals separately. We found that both anodal tDCS and α-tACS significantly (P < 0.05) reduced subjective fatigue and improved accuracy on the test task compared to the blank group, and the extent of change was greater with tACS. For the HRV features extracted from ECG signals. After tACS intervention, SDNN (t = -3.241, P = 0.002), LF (t = -3.511, P = 0.001), LFn (t = -3.122, P = 0.002), LFn/HFn (-2.928, P = 0.005), TP (t = -2.706, P = 0.008), VLF (t = -3.002, P = 0.004), SD2 (t = -3.594, P = 0.001) and VLI (t = -3.564, P = 0.001) showed a significant increasing trend, and HFn (t = 3.122, P = 0.002), SD1/SD2 (t = 3.158, P = 0.002) and CCM_1 (t = 3.106, P = 0.003) showed a significant decreasing trend. After tDCS intervention, only one feature, TINN, showed a significant upward trend (P < 0.05). The other features showed non-significant changes but roughly the same trend as the tACS group. Both tDCS and α-tACS can be effective in relieving mental fatigue, and α-tACS is more effective than tDCS. This study provides theoretical support for tDCS with α-tACS having a alleviating effect on mental fatigue and the use of ECG as a valid objective assessment tool.

Associations between TCA cycle plasma metabolites and fatigue in black females with systemic lupus erythematosus: An untargeted metabolomics pilot study.

In this pilot study, we used untargeted metabolomics to identify biochemical mechanisms or biomarkers potentially underlying SLE-related fatigue. Metabolon conducted untargeted metabolomic plasma profiling using ultrahigh performance liquid chromatography/tandem mass spectrometry on plasma samples of 23 Black females with systemic lupus erythematosus (SLE) and 21 no SLE controls. Fatigue phenotypes of general fatigue, physical fatigue, mental fatigue, reduced activity, and reduced motivation were measured with the reliable and valid Multidimensional Fatigue Inventory (MFI). A total of 290 metabolites were significantly different between the SLE and no SLE groups, encompassing metabolites related to glycolysis, TCA cycle activity, heme catabolism, branched chain amino acids, fatty acid metabolism, and steroids. Within the SLE group, controlling for age and co-morbidities, TCA cycle metabolites of alpha-ketoglutarate (AKG) and succinate were statistically significantly associated (p < .05) with physical and general fatigue. While pervasive perturbations in the entire TCA cycle have been implicated as a potential mechanism for fatigue, our results suggest individual metabolites of AKG and succinate may be potential biomarkers or targets of intervention for fatigue symptom management in SLE. Additionally, perturbations in heme metabolism in the SLE group provide additional insights into mechanisms that promote systemic inflammation.

Individual Variability in Brain Connectivity Patterns and Driving-Fatigue Dynamics.

Mental fatigue during driving poses significant risks to road safety, necessitating accurate assessment methods to mitigate potential hazards. This study explores the impact of individual variability in brain networks on driving fatigue assessment, hypothesizing that subject-specific connectivity patterns play a pivotal role in understanding fatigue dynamics. By conducting a linear regression analysis of subject-specific brain networks in different frequency bands, this research aims to elucidate the relationships between frequency-specific connectivity patterns and driving fatigue. As such, an EEG sustained driving simulation experiment was carried out, estimating individuals' brain networks using the Phase Lag Index (PLI) to capture shared connectivity patterns. The results unveiled notable variability in connectivity patterns across frequency bands, with the alpha band exhibiting heightened sensitivity to driving fatigue. Individualized connectivity analysis underscored the complexity of fatigue assessment and the potential for personalized approaches. These findings emphasize the importance of subject-specific brain networks in comprehending fatigue dynamics, while providing sensor space minimization, advocating for the development of efficient mobile sensor applications for real-time fatigue detection in driving scenarios.

A Spanish version of the Three-Dimensional Work Fatigue Inventory (3D-WFI): factor structure, internal consistency, and criterion validity

BackgroundIn the working population, there are risks of overload due to physical, mental, and emotional demands. No instrument is available in Spanish to measure these three types of work fatigue (WF) separately. This paper adapts the Three-Dimensional Work Fatigue Inventory (3D-WFI) (2015), which is of American origin and measures and differentiates these three different types of WF. It has adequate psychometric properties at its root, as do the subsequent German (2018), Lebanese (2022), and Chinese (2023) adaptations.MethodsA total of 1100 workers (average age = 40 years) from economic sectors such as security and transportation of valuables, secondary and university educational institutions, and healthcare centers participated. They responded to the 3D-WFI, the Health-Related Quality of Life Index, and the Individual Strength Checklist for concurrent validity effects, together with items with sociodemographic and lifestyle variables.ResultsA confirmatory factor analysis with the total sample 3D-WFI supports its three-dimensionality; Cronbach’s alpha and Omega values are adequate by dimensions: for physical work fatigue (α = 0.92, Ω = 0.92), for mental work fatigue (α = 0.94. Ω = 0.94), and emotional work fatigue (α = 0.95, Ω = 0.95). The 3D-WFI correlates significantly with the Checklist Individual Strength (0.743), and a pattern of significant relationships is found between WF and antecedent variables (e.g., being exposed to heat and noise, emotional labor, concentration, and workwear), as well as some consequences of WF (for example, mental health, absenteeism, work satisfaction, and sleep quality).ConclusionsWe contribute here to the cross-cultural validity of the 3D-WFI, which can be used reliably and validly in the Chilean and probably Latin American working population. Some WF predictor variables are confirmed, as well as WF impacts on the absenteeism, health, and quality of life among workers.

Adaptation and Validation of the Turkish Version of the Brain Fog Scale.

Brain fog is a condition that is characterized by poor concentration, memory loss, decreased cognitive function, and mental fatigue. Although it is generally known as a long-term COVID-19 symptom, brain fog has also been reported to be caused by many other diseases. Thus, it is necessary to assess this condition in certain populations. This study aimed to evaluate the reliability and validity of the Brain Fog Scale in a Turkish population. We conducted the study in two phases. In a pilot study including 125 participants, we confirmed the suitability of the scale for validity analyses and then conducted exploratory (n = 230) and confirmatory factor analyses (n = 343). The Cronbach's alpha value of the 23-item Brain Fog Scale was 0.966. In addition, the 23-item and three-factor structure was confirmed as a result of the analyses. These three factors are mental fatigue, impaired cognitive acuity, and confusion. We also found that participants previously diagnosed with COVID-19 had higher brain fog scores. This finding indicates that brain fog is an important condition that can accompany COVID-19. Furthermore, this validated construct has an acceptable fit and is a valid and useful tool for the Turkish population.

Experiences of family caregivers in the home care to people with pressure injuries

Objectives: To analyze the experience of family caregivers in the home care for people with pressure injuries (PI). Methods: Qualitative and descriptive research carried out with family members who received support from the home care service and who were the main informal caregivers of people with PI from stage 3 onwards. A sociodemographic questionnaire and semi-structured interview were applied with the following stimulus for narration: tell me about your experience in the home care to your family member with PI? Data were analyzed according to Bardin's content analysis. Results: Four categories emerged: 1) Performance of family members in PI care; 2) Support of the home care service to the family and patients with PI; 3) Overload of family caregivers; 4) Satisfaction in repaying the care received. Conclusion: This study showed the importance of support to home care service and the difficulties experienced by family members in caring for people with PI, including financial and physical overload; lack of preparation of the caregiver to deal with PI; family conflicts; and the centralization of care responsibility, predominantly performed by women. However, many see in care the opportunity to return the love received, despite all physical and mental fatigue.