Recent scholarly efforts have sought to examine the cumulative impact of deleterious adverse childhood exposures on various mental health outcomes. Lifetime prevalence rates for depressive disorders are approximately 20% among adolescents. Depression is ranked as the leading cause for disability and fourth leading contributor to the global burden of disease in the world. The purpose of this study was to determine the cumulative impact of adolescent adverse experiences on outcomes of depression, suicide ideation, and overall mental distress in a cohort of 125 adolescent girls receiving public assistance. The adverse exposures studied were personal victimization, household dysfunction, and community violence exposures. Across the three categories of exposures, adolescents reported that community exposures were the highest 92.8%, followed by household dysfunction 89.6 %, and lastly, personal victimization 80%. Over 40% reported experiencing more than seven adverse exposures. There was a doubling in the incidence of depression by the fourth year, and an almost ten percent increase in mental distress by the fourth year. Evidence of a significant direct association was found for those experiencing victimization with depression and suicide ideation. The total Adolescent Adverse Exposures (AAE) score was positively correlated with the CES-D scores in the last three years of the study, however not with suicide ideation. The cumulative impact or 'dose-response' relationship of such exposures on depression, suicide ideation, or change over time was not found. In contradiction with general beliefs and existing literature, a significant negative association was found with depression and having a parent incarcerated or experiencing the divorce of parents. This finding suggests given the homogeneity of this population, experiencing both poverty and high levels of exposure to victimization, that having an incarcerated parent or parental divorce may be potentially protective mitigating the stressful experiences of continued victimization. The results of this study offer evidence of high prevalence rates of adversity occurring in the lives of these already at risk adolescents. A call for efforts to reduce community violence and personal victimization in the context of poverty are needed to prevent the growing rates of depression and suicide ideation for these fragile families and adolescence.

<p>Surface electromyography (sEMG) has been used to monitor muscle activity and predict fatigue in the workplaces. However, objectively measuring fatigue is challenging in complex work with unpredictable work cycles, where sEMG may be influenced by the dynamically changing posture demands. The sEMG is affected by various variables and substantial change in mean power frequencies (MPF), and a decline over 8-9% is primarily considered musculoskeletal fatigue. These MPF thresholds have been frequently used, and there were limited efforts to test their appropriateness in determining musculoskeletal fatigue in live workplaces (which predominantly consist of complex tasks). In addition, the techniques that consider both muscular and postural measurements that incorporate dynamic posture changes observed in complex work have not yet been explored. The overall objective of this work is to leverage both postural and muscular cues to identify musculoskeletal fatigue in complex tasks/jobs (i.e., tasks involving different levels of exertions, durations, and postures). The work was completed in two studies.</p> The first study aimed to (1) predict subjective fatigue using objective measurements in non-repetitive tasks, (2) determine whether the musculoskeletal fatigue thresholds in non-repetitive tasks differed from the previously reported threshold, and (3) utilize the empirically calculated thresholds to test their appropriateness in determining musculoskeletal fatigue in live surgical workplaces. The findings showed that the multi-modal measurements indicate better sensitivity than single-modality (sEMG) measurements in detecting decreases in MPF, a predictor of fatigue. In addition, the results showed that the thresholds in dynamic non-repetitive tasks, like surgery, are different than the previously reported 8% threshold. Additionally, implementing muscle-specific thresholds increased the likelihood of more accurately reporting subjective fatigue. The second study aimed to develop a multi-modal fatigue index to detect musculoskeletal fatigue. A controlled laboratory study was performed to simulate the non-repetitive physical demands at different postures. A series of experiments were conducted to test the effectiveness of various metrics/models to identify subjective fatigue in complex tasks. Next, the composite fatigue index (CFI) function was developed using the time-synced integration of both muscular signals (measured with sEMG sensors) and postural signals (measured with Inertial Measurement Unit (IMU) sensors). The variables from sEMG (amplitude, frequency, and the number of muscles showing signs of fatigue) and IMU (the prevalence of static and demanding postures and the number of shoulders in static/demanding posture) sensors were integrated to generate the CFI function. The prevalence of static/demanding postures was developed using the cumulative exposures to static/demanding postures based on the material fatigue failure theory. The single value fatigue index was obtained using the resultant CFI function, which incorporates both muscular and postural variables, to quantify the muscular fatigue in dynamic non-repetitive tasks. The findings suggested that the propagation of musculoskeletal fatigue can be detected using the multi-modal composite fatigue index in complex tasks. The resultant CFI function was then applied to surgery tasks to differentiate the fatigued and non-fatigued groups. The findings showed that the multi-modal fatigue assessment techniques could be utilized to incorporate the muscular and postural measurements to identify fatigue in complex tasks beyond single-modality assessment approaches.