Do Changes in Mental Energy and Fatigue Impact Functional Assessments Associated with Fall Risks? An Exploratory Study Using Machine Learning

Age and Type of Task-Based Impact of Mental Fatigue on Balance: Systematic Review and Meta-Analysis

The role of cognition in balance control suggests that mental fatigue may negatively affect balance. However, cognitive involvement in balance control varies with the type or difficulty of the balance task and age. Steady-state balance tasks, such as quiet standing, are well-learned tasks executed automatically through reflex activities controlled by the brainstem and spinal cord. In contrast, novel, and challenging balance tasks, such as proactively controlling balance while walking over rugged terrain or reacting to unexpected external perturbations, may require cognitive processing. Furthermore, individuals with preexisting balance impairments due to aging or pathology may rely on cognitive processes to control balance in most circumstances. This systematic review and meta-analysis investigated the effect of mental fatigue on different types of balance control tasks in young and older adults. A literature search was conducted in seven electronic databases and 12 studies met eligibility criteria. The results indicated that mental fatigue had a negative impact on both proactive (under increased cognitive load) and reactive balance in young adults. In older adults, mental fatigue affected steady-state and proactive balance. Therefore, mentally fatigued older individuals may be at increased risk of a loss of balance during steady-state balance task compared to their younger counterparts.

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.

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.

Fatigue Effect on Minimal Toe Clearance and Toe Activity during Walking

This study investigates the effects of fatigue on the process of walking in young adults using the developed clog-integrated sensor system. The developed sensor can simultaneously measure the forefoot activity (FA) and minimum toe clearance (MTC). The FA was evaluated through the change in the contact area captured by a camera using a method based on a light conductive plate. The MTC was derived from the distance between the bottom surface of the clog and ground obtained using a time of flight (TOF) sensor, and the clog posture was obtained using an acceleration sensor. The induced fatigue was achieved by walking on a treadmill at the fastest walking speed. We evaluated the FA and MTC before and after fatigue in both feet for 14 participants. The effects of fatigue manifested in either the FA or MTC of either foot when the results were evaluated by considering the participants individually, although individual variances in the effects of fatigue were observed. In the dominant foot, a significant increase in either the FA or MTC was observed in 13 of the 14 participants. The mean MTC in the dominant foot increased significantly (p = 0.038) when the results were evaluated by considering the participants as a group.

The acute effects of mental fatigue on balance performance in healthy young and older adults - A systematic review and meta-analysis

Cognitive resources contribute to balance control. There is evidence that mental fatigue reduces cognitive resources and impairs balance performance, particularly in older adults and when balance tasks are complex, for example when trying to walk or stand while concurrently performing a secondary cognitive task. We conducted a systematic literature search in PubMed (MEDLINE), Web of Science and Google Scholar to identify eligible studies and performed a random effects meta-analysis to quantify the effects of experimentally induced mental fatigue on balance performance in healthy adults. Subgroup analyses were computed for age (healthy young vs. healthy older adults) and balance task complexity (balance tasks with high complexity vs. balance tasks with low complexity) to examine the moderating effects of these factors on fatigue-mediated balance performance. We identified 7 eligible studies with 9 study groups and 206 participants. Analysis revealed that performing a prolonged cognitive task had a small but significant effect (SMDwm = -0.38) on subsequent balance performance in healthy young and older adults. However, age- and task-related differences in balance responses to fatigue could not be confirmed statistically. Overall, aggregation of the available literature indicates that mental fatigue generally reduces balance in healthy adults. However, interactions between cognitive resource reduction, aging and balance task complexity remain elusive.

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.

Using Sensor Graphs for Monitoring the Effect on the Performance of the OTAGO Exercise Program in Older Adults

The OTAGO exercise program is effective in decreasing the risk for falls of older adults. This research investigated if there is an indication that the OTAGO exercise program has a positive effect on the capacity and as well as on the performance in mobility. We used the data of the 10-months observational OTAGO pilot study with 15 (m = 1, f = 14) (pre-)frail participants aged 84.60 y (SD: 5.57 y). Motion sensors were installed in the flats of the participants and used to monitor their activity as a surrogate variable for performance. We derived a weighted directed multigraph from the physical sensor network, subtracted the weights of one day from a baseline, and used the difference in percent to quantify the change in performance. Least squares was used to compute the overall progress of the intervention (n = 9) and the control group (n = 6). In accordance with previous studies, we found indication for a positive effect of the OTAGO program on the capacity in both groups. Moreover, we found indication that the OTAGO program reduces the decline in performance of older adults in daily living. However, it is too early to conclude causalities from our findings because the data was collected during a pilot study.

Deriving Mental Energy From Task Completion

Many tasks in everyday life (e.g., making an accurate decision, completing job tasks, and searching for product information) are extrinsically motivated (i.e., the task is performed to gain a benefit) and require mental effort. Prior research shows that the cognitive resources needed to perform an extrinsically motivated task are allocated pre-task. The pre-task allocation of mental resources tends to be conservative, because mental effort is costly. Consequently, there are mental energy deficits when the use of mental resources exceeds the allocated amount. This research provides evidence for post-task mental energy replenishment. The amount of resource replenishment is a function of the size of the mental energy deficit and the favorability of the cost-benefit trade-off experienced at the completion of the task (i.e., the value of the reward given the energy investment). The findings have implications for how cognitive resources management influences the availability of mental energy on a moment-to-moment basis.

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.