Sleep quality and sex modify the relationships between trait energy and fatigue on state energy and fatigue

Depression, Anxiety, Energy, and Fatigue Among Nurses Who Cared for Patients During the COVID-19 Pandemic: A Cross-Sectional Study

Purpose of Study: Nurses around the world have faced challenges during the coronavirus disease 2019 (COVID-19) pandemic. This study examined the association between depression and anxiety and trait energy and trait fatigue, and baseline health status and work characteristics. Design of Study: A cross-sectional study. Methods: A survey was conducted to collect self-reported data from nurses involved in patient care in Northern Virginia. Depression and anxiety were assessed using the Patient-Reported Outcomes Measurement Information System (PROMIS) depression and anxiety scales. To measure trait energy and trait fatigue, the Mental and Physical State and Trait Energy and Fatigue Scale (MPSTEFS) was used. Findings: There was a significant association between depression and energy (b=-0.46, t = -1.78, p < .001) and loneliness (b=1.38, t = 4.00, p < .001) and increased alcohol use (b=2.11, t = 2.04, p = .045). We also found that nurses with depression were significantly more likely to seek mental health counseling (b=-2.91, t = 2.54, p = 0.013), which was also the case for anxiety (b=3.13, t = 2.14, p = .036). Conclusions: Our study highlights the mental health burden among nurses who worked in the early phase of the COVID-19 pandemic and its association with increased alcohol use and loneliness. The findings may help healthcare leaders identify early signals of deterioration in nurses' well-being.

Multidimensional Model of Energy in Patients With Cancer

OBJECTIVES

Evidence suggests that energy is a distinct symptom from fatigue in patients with cancer. The purpose of this paper is to present the Multidimensional Model of Energy in Patients with Cancer (MMEPC) that is based on emerging evidence and to make recommendations for clinical practice and future research.

METHODS

The literature was reviewed to determine various factors associated with variations in energy in patients with cancer. In addition, some of the emerging evidence in the model is supported by studies of energy in the general population and in patients with other chronic conditions.

RESULTS

Based on a review of the literature, specific concepts in the MMEPC include: person factors, clinical factors, cancer-related factors, biological factors, factors associated with energy balance, and co-occurring symptoms. The evidence to support the association between each of these factors and variations in energy levels in patients with cancer is described and synthesized.

CONCLUSION

This article provides emerging evidence on factors that influence variations in energy levels in patients with cancer. While the fundamental biobehavioral and biologic mechanisms that underlie variations in energy levels are not well understood, the model can be used to design pre-clinical and clinical studies of energy in patients with cancer. In addition, while emerging evidence supports the hypothesis that fatigue and energy are distinct symptoms, additional research on common and distinct risk factors and underlying mechanisms is warranted to be able to develop and test precision interventions for one or both symptoms.

IMPLICATIONS FOR NURSING PRACTICE

The risk factors (eg, being female, sleep quality) associated with variations in energy levels in patients with cancer identified in this paper have important clinical implications. Clinicians can use the identified risk factors to guide their assessments; identify high-risk patients with decrements in energy decrement; and develop targeted energy conservation interventions for the patients.

Fatigue and cognitive fatigability in patients with chronic pain

OBJECTIVES

Fatigue is common in patients with chronic pain. Still, there is a lack of studies examining objectively measurable cognitive aspects of fatigue: cognitive fatigability (CF). We aimed to investigate the presence of CF in patients with chronic pain and its relation to self-rated fatigue, attention, pain characteristics, sleep disturbance, depression, and anxiety.

METHODS

Two hundred patients with chronic pain and a reference group of 36 healthy subjects underwent a comprehensive neuropsychological test battery, including measurement of CF with the Wechsler Adult Intelligence Scale-III Coding subtest, and self-assessment of trait and state fatigue.

RESULTS

The patients with chronic pain did not show more CF as compared to the reference group. There was an association between CF and processing speed on a test of sustained and selective attention in the chronic pain group, while self-rated fatigue measures and pain characteristics were not associated with CF. Self-rated fatigue measures were highly correlated with self-rated pain intensity, spreading of pain, depression, anxiety, and sleep disturbance.

CONCLUSIONS

The findings highlight the distinction between objective and subjective aspects of fatigue in chronic pain, and that the underlying causes of these different aspects of fatigue need to be studied further.

Fatigue and resilience in Master's and PhD students in the Covid-19 pandemic in Brazil: A cross-sectional study

The aim of this study was to analyze levels of fatigue and resilience of Brazilian graduate students during the COVID-19 pandemic and to determine whether there is an association between fatigue and resilience and sociodemographic and academic factors. Data were analyzed using descriptive and inferential statistics, and it was discovered that the variables associated with higher levels of resilience were age; having children; being retired; receiving income above five minimum wages; having had greater problems in other phases of the research schedule; coming from private universities; being from the north of Brazil; studying the area of Health; and having their research schedule unaffected during the pandemic. On the other hand, lack of resilience was associated with not having children; being less well-off financially; being younger; being a woman; studying in a public university; and having to postpone part of the research during the pandemic. The conclusion of the study indicated the need for graduate programs to design strategies to deal with fatigue and promote resilience in Master's and PhD students.

Longitudinal Associations Between Higher Self-Reported Energy, Gait Speed, and Cognition in Older Adults With Fatigue

BACKGROUND

Older adults reporting higher energy levels have better physical function. It is not known if these associations persist among older adults reporting fatigue or if higher energy is associated with cognitive function. We examined longitudinal associations between self-reported energy, gait speed, and cognition, stratified by fatigue, in 2 613 participants (aged 74.6 ± 2.87 years) in the Health, Aging and Body Composition Study.

METHODS

Self-reported energy (0-10, dichotomized at median) and fatigue (present/absent) were measured at baseline. Usual and rapid-paced gait speed (m/s), modified Mini-Mental State Examination (3MS), and Digit Symbol Substitution Test (DSST) were measured at baseline and annually over 8 years. Linear mixed effect models compared changes in gait speed, 3MS, and DSST between higher and lower energy groups within fatigue strata.

RESULTS

At baseline, 724 participants (27%) were fatigued; 240 (33%) coreported higher energy (9% of total). The remaining 1 889 participants were fatigue-free (73%); 1 221 (65%) coreported higher energy (47% of total). Those with fatigue and higher energy had average rapid gait declines of 0.007 m/s per year (p = .04) after adjustment for demographics, comorbidities, depressive symptoms, and exercise. DSST declines were found among only fatigue-free participants (β = 0.17, p = .01). No statistically significant associations with energy were found for fatigue-free participants, or for usual gait or 3MS.

CONCLUSIONS

Asking about older adults' energy levels as well as fatigue may identify a subgroup of older adults protected against physical and cognitive decline, even among those with fatigue.

Correlates of depressive mood among graduate-level allied health students: An exploratory study examining trait energy and fatigue

Objective: The objective of this study was to identify factors associated with the occurrence and severity of depressive mood states among graduate-level allied health students. Participants: Students (N = 77) completed this study. Methods: Participants completed a series of self-reported surveys measuring moods, lifestyle behaviors, trait mental and physical energy and fatigue, and objective assessments of Trail-Making Test Part-B, and muscle oxygen consumption. Multiple backwards linear regression models were fitted to identify factors associated with depressive mood states. Results: When accounting for all subjects, increased severity of depressive mood states was associated with worse sleep quality (SQ), increased sitting time (ST), and trait physical fatigue (TPF). When examining subjects reporting depressive mood states, increased severity of depressive mood states was associated with worse SQ, increased ST, decreased mental workload on non-school days, and trait physical energy (TPE). Conclusion: Adjustments in lifestyle factors such as sleep, mental workload, and ST, may ameliorate depressive mood states.

Sex predicts post-concussion symptom reporting, independently of fatigue and subjective sleep disturbance, in premorbidly healthy adults after mild traumatic brain injury

The relationship between sex and post-concussion symptom (PCS) reporting after mild traumatic brain injury (mTBI) is not well understood. Subjective sleep disturbance and fatigue impact PCS reporting after mTBI and show sex differences in the normal population. This study investigated whether sex had a relationship with PCS reporting after mTBI, independently of self-reported sleep disturbance and fatigue. Ninety-two premorbidly healthy adults in the post-acute period after mTBI completed the Rivermead Post-Concussion Symptoms Questionnaire, the Pittsburgh Sleep Quality Index, the Multidimensional Fatigue Inventory and measures of depression, anxiety and post-traumatic stress symptomatology. Females (n = 23) demonstrated higher levels of fatigue (p = .019) and greater psychological distress (p = .001) than males (n = 69), but equivalent levels of sleep disturbance (p = .946). Bootstrapping analyses were undertaken because PCS responses were not normally distributed. Female sex predicted greater PCS reporting (p = .001), independently of subjective sleep disturbance, fatigue, psychological distress and litigation status. The current findings support and extend previous work showing premorbidly healthy females are at higher risk of experiencing elevated PCS after mTBI than males in the post-acute period after mTBI. It may be beneficial for clinicians to be particularly sensitive to increased symptom reporting after mTBI in females, irrespective of sleep quality, fatigue or psychological status.

Preventive Medicine via Lifestyle Medicine Implementation Practices Should Consider Individuals' Complex Psychosocial Profile

Noncommunicable chronic diseases are associated with lifestyle behaviors. Psychological and social factors may influence the adoption of such behaviors. Being mentally and physically energized or fatigued may influence the intention-behavior gap of healthy lifestyle adoption accordingly. We investigated the associations of age, sex, lifestyle behaviors, mood, and mental and physical energy and fatigue at both the trait and state levels. The participants (N = 670) completed questionnaires assessing their sleep, mood, mental and physical state energy and fatigue, physical activity, mental workload, and diet. The ordinary least squares regression models revealed an overlap between the mental state and trait energy levels for males who consume polyphenols, have a high mental workload, and sleep well. Being younger, having a high stress level, bad sleep habits, and being confused and depressed were associated with high mental fatigue. Physical energy and fatigue shared the same commonalities with the previous results, with greater discrepancies observed between the state and trait indicators compared to that between mental energy and fatigue. Diet and stress management seem to be predictors of high physical energy, and females report higher physical fatigue levels. Health care professionals should consider this psychosocial complex profiling in their differential diagnosis and when one is implementing lifestyle behavioral changes to address the facets of preventive medicine, wellness, and health promotion.

Factors Influencing Motivation to Perform Mental and Physical Tasks During the Initial Lockdown Period of the COVID-19

Drastic changes to lifestyles have occurred during the COVID-19 pandemic. An unintended consequence of stay at home orders is increased isolation and less social interaction for many people. For overall wellbeing it is important to stay both physically and mentally active; however, for many individual's motivation may be a barrier. There are non-modifiable (e.g. sex, age, personality, infection rates in the area) and modifiable factors (e.g. physical activity, diet, sleep) that may be associated with motivation to perform physical and mental tasks. We collected data from 794 subjects using an online survey between April 13th to May 3rd of 2020. Survey questionnaires included demographics, personality traits, diet, sleep, physical activity levels, mental workload and motivation to perform mental and physical tasks. Multiple linear regression analyses were used to assess the association between non-modifiable and modifiable variables on motivation to perform mental and physical tasks. The results of our analyses suggest that those who reported a higher quality of diet (REAP-S score), exercised vigorously, and reduced their sedentary time, reported higher motivation to perform both mental and physical tasks. Those who were employed and had higher grit were more motivated to perform physical tasks. Lower trait physical energy was associated with greater motivation to perform mental tasks. Our findings support that during challenging times, such as the COVID-19 pandemic, it is important for healthcare practitioners to emphasize the importance healthy lifestyle behaviors to prevent individuals from experiencing a lack of motivation to perform both mental and physical tasks. Future research should focus on trying to determine the directionality of the relationship between specific healthy lifestyle behaviors and motivation.

Effectiveness of Digital Cognitive Behavior Therapy for the Treatment of Insomnia: Spillover Effects of dCBT

The effects of digital Cognitive Behavior Therapy for insomnia (dCBT-i) on sleep quality have been previously demonstrated but the spillover effects on fatigue, flow (a state of immersion in activities of interest), and cognitive flexibility remain unclear. The current study examined the effectiveness of dCBT-i. A total of 97 college students (20.96 ± 1.87 years, 73.1% female students) were randomly selected from a shortlist and divided into sleep intervention (n = 39), conventional education (n = 37), and healthy control (n = 21) groups. Task switching paradigm, Fatigue Severity Scale (FSS), Flow Experience Scale (FES), and the Chinese version of the Pittsburgh Sleep Quality Index (CPSQI) were measured pre- and post-intervention. Results show that the sleep quality of the intervention group improved, and fatigue was relieved. Participants in the sleep intervention group had increased flow experience scores post-intervention and improved cognitive flexibility. The control group’s sleep quality deteriorated and fatigue level increased. dCBT-i can not only achieve a significant improvement in sleep quality and reduce fatigue, but also improve learning abilities, quality of life, flow, and cognitive flexibility. Future research should pay attention to indicators such as work efficiency, sedative use, and the durability and stability of such effects.

The Effect of Chronic Exercise on Energy and Fatigue States: A Systematic Review and Meta-Analysis of Randomized Trials

In this meta-analysis, we synthesized the results of randomized controlled trials of different exercise training interventions on participants' feelings of fatigue, energy, and vitality. The search of studies was conducted using six databases as well as several other supplementary search strategies available before December 2021. The initial search generated over 3,600 articles with 81 studies (7,050 participants) and 172 effects meeting the inclusion criteria. We analyzed the effects from the studies using a meta-analytic multivariate model and considered the potential moderating effect of multiple variables. Our analysis revealed exercise to decrease the feelings of fatigue by a small effect size (g = -0.374; 95% CI [-0.521, -0.227]), increase energy by a small-to-moderate effect size (g = 0.415; 95% CI [0.252, 0.578]), and to increase the feeling of vitality by a moderate effect size (g = 0.537; 95% CI [0.404, 0.671]). All main results remained robust after several sensitivity analyses using different statistical estimators, and consideration of outlier and influential studies. Moreover, moderator analyses revealed significant effects of exercise intensity and intervention duration on fatigue, exercise intensity, and modality on energy, and participant health, exercise intensity modality, and exercise training location on vitality. We conclude that when groups adopt a moderate intensity exercise training program while participating in a randomized trial, compared to controls, this typically results in small-to-moderate average improvements in feelings of fatigue, energy, and vitality.

Fatigue Across the Lifespan in Men and Women: State vs. Trait

Objective

Fatigue is commonly thought to worsen with age, but the literature is mixed: some studies show that older individuals experience more fatigue, others report the reverse. Some inconsistencies in the literature may be related to gender differences in fatigue while others may be due to differences in the instruments used to study fatigue, since the correlation between state (in the moment) and trait (over an extended period of time) measures of fatigue has been shown to be weak. The purpose of the current study was to examine both state and trait fatigue across age and gender using neuroimaging and self-report data.

Methods

We investigated the effects of age and gender in 43 healthy individuals on self-reported fatigue using the Modified Fatigue Impact Scale (MFIS), a measure of trait fatigue. We also conducted fMRI scans on these individuals and collected self-reported measures of state fatigue using the visual analog scale of fatigue (VAS-F) during a fatiguing task.

Results

There was no correlation between age and total MFIS score (trait fatigue) (r = –0.029, p = 0.873), nor was there an effect of gender [F_(1,31) < 1]. However, for state fatigue, increasing age was associated with less fatigue [F_(1,35) = 9.19, p < 0.01, coefficient = –0.4]. In the neuroimaging data, age interacted with VAS-F in the middle frontal gyrus. In younger individuals (20–32), more activation was associated with less fatigue, for individuals aged 33–48 there was no relationship, and for older individuals (55+) more activation was associated with more fatigue. Gender also interacted with VAS-F in several areas including the orbital, middle, and inferior frontal gyri. For women, more activation was associated with less fatigue while for men, more activation was associated with more fatigue.

Conclusion

Older individuals reported less fatigue during task performance (state measures). The neuroimaging data indicate that the role of middle frontal areas change across age: younger individuals may use these areas to combat fatigue, but this is not the case with older individuals. Moreover, these results may suggest greater resilience in females than males when faced with a fatiguing task.

Trait Energy and Fatigue Modify Acute Ingestion of an Adaptogenic-Rich Beverage on Neurocognitive Performance

Background: Psychological research considers traits as a long-standing pre-disposition to an individual’s mood, whereas short-term feelings are categorized as states. We previously reported similar overall acute mental performance benefits between an adaptogen-rich, caffeine-containing energy shot (e+Energy Shot–e+Shot; Isagenix International, LLC) and a caffeine-matched placebo Since the publication of that study, multiple studies have reported that trait mental and physical energy (TME/TPE), and trait mental and physical fatigue (TMF/TPF) status modify the effect of various interventions on neurocognitive performance. Therefore, we reevaluated our previously published work and accounted for the four traits. Methods: Participants (n = 30) completed a series of questionnaires to determine baseline trait energy and fatigue measures. Then, participants performed a 27 min battery of neurocognitive tasks before and three times after consuming the study beverages with 10 min breaks between each post-consumption battery of tests. Data from the previous study were re-analyzed using linear mixed-effects models. Results: We now report that the adaptogen product significantly improved mood and cognitive test responses in individuals stratified by initial TME, TPE, TMF, and TPF status. Moreover, this reevaluation also indicated that the caffeine placebo significantly increased heart rate and blood pressure in those subjects initially characterized by low physical and mental energy. Conclusions: In summary, a post-hoc re-analysis of our initial study suggests that consumption of the adaptogen-rich, caffeine-containing product preferentially benefited individuals with initial low TME/TPE and high TMF status when compared to caffeine alone. These findings also support our previous study suggesting that adaptogens may promote mental and physical performance benefits while modulating potentially negatively associated responses to caffeine.

Using Machine Learning to Identify Feelings of Energy and Fatigue in Single-Task Walking Gait: An Exploratory Study

The objective of this study was to use machine learning to identify feelings of energy and fatigue using single-task walking gait. Participants (n = 126) were recruited from a university community and completed a single protocol where current feelings of energy and fatigue were measured using the Profile of Moods Survey–Short Form approximately 2 min prior to participants completing a two-minute walk around a 6 m track wearing APDM mobility monitors. Gait parameters for upper and lower extremity, neck, lumbar and trunk movement were collected. Gradient boosting classifiers were the most accurate classifiers for both feelings of energy (74.3%) and fatigue (74.2%) and Random Forest Regressors were the most accurate regressors for both energy (0.005) and fatigue (0.007). ANCOVA analyses of gait parameters comparing individuals who were high or low energy or fatigue suggest that individuals who are low energy have significantly greater errors in walking gait compared to those who are high energy. Individuals who are high fatigue have more symmetrical gait patterns and have trouble turning when compared to their low fatigue counterparts. Furthermore, these findings support the need to assess energy and fatigue as two distinct unipolar moods as the signals used by the algorithms were unique to each mood.

Trait Energy and Fatigue May Be Connected to Gut Bacteria among Young Physically Active Adults: An Exploratory Study

Recent scientific evidence suggests that traits energy and fatigue are two unique unipolar moods with distinct mental and physical components. This exploratory study investigated the correlation between mental energy (ME), mental fatigue (MF), physical energy (PE), physical fatigue (PF), and the gut microbiome. The four moods were assessed by survey, and the gut microbiome and metabolome were determined from 16 S rRNA analysis and untargeted metabolomics analysis, respectively. Twenty subjects who were 31 ± 5 y, physically active, and not obese (26.4 ± 4.4 kg/m2) participated. Bacteroidetes (45%), the most prominent phyla, was only negatively correlated with PF. The second most predominant and butyrate-producing phyla, Firmicutes (43%), had members that correlated with each trait. However, the bacteria Anaerostipes was positively correlated with ME (0.048, p = 0.032) and negatively with MF (−0.532, p = 0.016) and PF (−0.448, p = 0.048), respectively. Diet influences the gut microbiota composition, and only one food group, processed meat, was correlated with the four moods—positively with MF (0.538, p = 0.014) and PF (0.513, p = 0.021) and negatively with ME (−0.790, p < 0.001) and PE (−0.478, p = 0.021). Only the Firmicutes genus Holdemania was correlated with processed meat (r = 0.488, p = 0.029). Distinct metabolic profiles were observed, yet these profiles were not significantly correlated with the traits. Study findings suggest that energy and fatigue are unique traits that could be defined by distinct bacterial communities not driven by diet. Larger studies are needed to confirm these exploratory findings.

Sex differences in the impact of state and trait fatigue on gait variability

Conditions requiring greater attention or cognitive control, such as fatigue, lead to changes in the motor performance of a task. Perceived fatigue refers to subjective feelings of fatigue, can be expressed as a state variable or trait characteristic and is influenced by demographic factors, such as sex. The purpose of this study was to determine how sex interacts with state and trait physical fatigue (PF) and mental fatigue (MF) to influence gait variability.

METHODS

123 healthy adults (77 female, 46 male), aged 18-36 years, completed the Mental and Physical State and Trait Energy and Fatigue Scale. Using a median split for each fatigue variable, participants were placed into "low" or "high" fatigue categories. Gait variability was defined as the asymmetry of lateral step variability (ALSV) and coefficient of variation (CV) of gait speed, stride length and double limb (DL) support during overground walking.

RESULTS

Males with low state PF had greater ALSV than females with low state PF (p = 0.05, η²_p = 0.07) and males with high state PF (p = 0.007, η²_p = 0.15). Females with high trait MF had greater CV of gait speed than females with low trait mental fatigue (p = 0.02, η²_p = 0.08). Males with low trait MF had greater CV of gait speed (p = 0.01, η²_p = 0.10) and stride length (p = 0.002, η²_p = 0.17) than females with low trait MF. CV of DL support did not vary based on fatigue level or sex (p ≥ 0.11).

CONCLUSIONS

There are sex-specific differences in the impact of state PF on asymmetry of lateral step variability and trait MF on the variability of gait speed and stride length.

State and Trait Fatigue and Energy Predictors of Postural Control and Gait

Compromised attentional resources during perceived fatigue has been suggested to alter motor control. The authors determined if measures of postural control and gait are predicted by state and trait physical and mental fatigue and energy, and how these relationships are modified by sex, sleep quality, and physical activity. Young adults (n = 119) completed the Modified Clinical Test of Sensory Integration, overground walking, and questionnaires to quantify fatigue and energy, sleep quality, and physical activity. Regression models indicated that trait fatigue, trait energy, and sleep quality were predictors of postural control (p ≤ .02, R2 ≥ .04). State fatigue, state energy, and sex were predictors of gait (p ≤ .05, R2 ≥ .03). While the variance explained was low (3-13%), the results demonstrate perceptions of fatigue and energy may influence posture and gait.

Trait Energy and Fatigue Modify the Effects of Caffeine on Mood, Cognitive and Fine-Motor Task Performance: A Post-Hoc Study

Multiple studies suggest that genetic polymorphisms influence the neurocognitive effects of caffeine. Using data collected from a double-blinded, within-participants, randomized, cross-over design, this study examined the effects of trait (long-standing pre-disposition) mental and physical energy and fatigue to changes in moods (Profile of Mood Survey-Short Form (POMS-SF), state mental and physical energy and fatigue survey), cognitive (serial subtractions of 3 (SS3) and 7 (SS7)), and fine-motor task (nine-hole peg test) performance after consuming a caffeinated beverage and a non-caffeinated placebo. Results indicate that trait mental and physical fatigue and mental energy modified the effects of caffeine on vigor, tension-anxiety, physical, and mental fatigue. Additionally, we report that those who were high trait physical and mental fatigue and low-trait mental energy reported the greatest benefit of caffeine on the SS3 and SS7, while those who were high trait mental and physical fatigue reported the greatest benefit of consuming caffeine on fine-motor task performance. The results of our study suggest that trait mental and physical fatigue and mental energy modify the acute effects of caffeine among a group of healthy, young adults and should be measured and controlled for by researchers who choose to study the effects of caffeine on acute moods and cognitive and fine-motor task performance.

The Effect of Mental Fatigue on Neuromuscular Function is Similar in Young and Older Women

The purpose of this study was to examine the effect of a mentally fatiguing task on neuromuscular function in young and older women. Neuromuscular measures were obtained prior to and following 20 min of a mentally fatiguing task. Maximal force output significantly decreased after the mental fatigue task (p = 0.02) and this was not different between age groups (p = 0.32). Increases in cortical silent period duration approached significance in both young and older groups (p = 0.06), suggesting that mental fatigue may cause increased cortical inhibition. Measures of peripheral neuromuscular function (contractile properties of the muscle, M-wave) did not change (p ≥ 0.09), suggesting that changes in force production with mental fatigue are more likely due to supraspinal than peripheral mechanisms. These findings provide further evidence of an interaction between mental fatigue and physical function.