Fatigue: Biomedicine, Health & Behavior - Volume 7, Issue 1, 2019

Titles and abstracts for the journal, Fatigue: Biomedicine, Health & Behavior, Volume 7, Issue 1, 2019.

Volume 7, Issue 1, 2019

 * A comparison of task-based mental fatigue between healthy males and females "Abstract - Background:The issue of cognitive sex differences has been a topic of interest for researchers for several decades. The present study investigated the relatively new area of sex differences in mental fatigue. Methods: Mental fatigue was evaluated via a modified visual analogue mood scale (VAMS) and Activation Deactivation Adjective Checklist (AD-ACL) before and after a task designed to induce mental fatigue. The participants performed a reaction time task in three blocks of 17 min, without any rest time between the blocks. Results: Mental fatigue increased after each 17-min block for both sexes with no significant differences between males and females (P = .54). Females had slower reaction time within the first block but slightly faster reaction time within the second and third blocks (P ≤ .001). Conclusion: Although no significant differences in mental fatigue between male and female groups were found, the results may suggest that task unfamiliarity had a more negative influence on reaction times in females than males."


 * Predictors of feelings of energy differ from predictors of fatigue "Abstract - Background:Studies examining energy and fatigue as a bipolar mood have focused on a single variable, usually fatigue, when studying these moods. Objective: The purpose of this study was to identify factors predicting feelings of energy and fatigue separately while simultaneously examining multiple domains related to these mood states in graduate health sciences students. Method: Seventy-seven participants were recruited from a Physician Assistant, Physical Therapy and Occupational Therapy program at a small school in Northern New York. Participants completed a series of surveys to measure mood, diet, mental work load intensity on school days and non-school days, and physical activity. Participants also completed the Trail-making Test Part B task on an iPad and their Resting Metabolic Rate (RMR) and muscle oxygen consumption mVO2 was measured. A backwards linear regression was used to determine the relationship between energy, fatigue and multiple variables. Results: The predictor variables accounted for 46.1% and 22.7% of the variance in fatigue and energy, respectively. More fatigue was associated with worse sleep quality, more time spent sitting and higher perceived intensity of mental workload on non-school days. More energy was associated with better sleep quality, higher muscle oxygen saturation, lower RMR, and faster psychomotor performance. Conclusion: The results of this study indicate that energy and fatigue are separate, yet overlapping constructs that are predicted with different accuracy by different variables. Our results indicate that small lifestyle changes may be necessary to improve feelings of fatigue but comprehensive interventions may be necessary to improve feelings of energy and fatigue."


 * An exploratory multivariate study examining correlates of trait mental and physical fatigue and energy"Abstract - Background: Mental and physical energy and fatigue can be assessed as either stable long-term traits or as a temporary state. Although researchers recognize the need to separate the two, most research has focused on state, leaving trait understudied. Therefore, the objective of this study was to apply demographic, lifestyle and psychosocial variables known to be associated with state fatigue and energy to examine predictors of trait mental and physical energy and fatigue. Methods: A convenience sample (N = 671) completed an online survey measuring mood, physical activity, mental workload, polyphenol (plant-based healthy micronutrients) consumption in the diet, and sleep quality. A multivariate multiple regression model was fit to simultaneously test associations between covariates for each four trait fatigue indicators. Results: Poor sleep quality was the only consistent predictor of both energy and fatigue (mental and physical), with confusion correlating with all but physical energy. Age and depression were predictors of mental and physical fatigue, but caffeine consumption was predicted by higher physical fatigue only. Mental workload and physical activity on off-days predicted physical energy only, while polyphenol consumption and BMI predicted mental energy only. Conclusions: Findings suggest that mental/ physical energy and fatigue may be separate constructs that can be treated as empirically distinct. The distinctions between physical and mental fatigue are less pronounced, needing further exploration. Subsequent research should explore other potentially important biopsychosocial sources of variation in trait mental and physical energy and fatigue."


 * Effect of technology addiction on academic success and fatigue among Turkish university students"Abstract - Background: Technology addiction can cause certain physical, mental, and social health problems. Purpose: This study was conducted to determine the effect of technology addiction levels on academic success and fatigue in university students in Turkey. Methods: 743 students continuing their undergraduate education at a single university participated in this descriptive correlational study. Data was collected using a Student Identification Form, The Problematic Mobile Phone Use Scale, the Internet Addiction Scale, and the Piper Fatigue Scale. Results: 9.8% of the students exhibited internet addiction risk, while internet addiction was detected in 0.7%. Compared to students showing no addiction symptoms, students who scored in the internet addicts’ category were found to have lower academic success averages and higher fatigue levels. It was found that smart phone addiction of students alone explained 5.8% of the total variance in fatigue levels while the internet addiction of students alone explained 6.8% of the total variance in fatigue levels. Conclusion: Although internet addiction was relatively low in this study, academic success was negatively affected in students categorized as internet addicted and fatigue increased alongside technology addiction, suggesting that internet addiction may be a predictor of fatigue. Educational initiatives could help to raise awareness on the negative relationship between technology addiction and academic success and its effects on physical and psychological health."


 * The role of mitochondria in ME/CFS: a perspective"Abstract: Chronic fatigue syndrome (CFS) also known as Myalgic encephalomyelitis (ME) is a debilitating disease, characterized by the symptom of severe fatigue. ME/CFS is a heterogeneous condition in both clinical presentation and disease duration. A diagnosis of ME/CFS is based on the exclusion of other diseases due to a current lack of known biomarkers for the disease. Patients may be split into categories based on the severity of their illness – mild, moderate and severe. Here we consider some of the recent advances in the understanding of mitochondrial dysfunction and mitochondrial DNA (mtDNA) variation that may have relevance to ME/CFS. Thus far, we have shown that ME/CFS patients do not harbor proven mtDNA mutations, another exclusion, albeit an important one. As such this group of patients do not fall within the category of patients with mitochondrial disorder. If ME/CFS patients have some form of mitochondrial dysfunction, the form and cause of this dysfunction is a matter of debate. The current data underlines the need to move from small studies to larger endeavors applying multiple methods to well-defined cohorts with samples taken longitudinally."