Key Research Areas include:
- Neuroscience; particularly cognitive mechanisms
- Physiology; and it's measurement and recording
- Psychophysiology; the relationship between physiological measures and psychological states.
- Diabetes; focussing on early detection
- Electrophysiological biomarkers for detection of disease states
Since 2016, I have helped to coordinate, administer, lecture and demonstrate the UTS subjects:
- Neuroscience (91706)
- Medical & Applied Physiology (91708)
In addition, I have also run practical classes/tutorials for the UTS subjects:
- Health and Homeostasis (91528)
- Pathophysiology and Pharmacology (91530)
I have also lectured and demonstrated to both first year, and second year medical students.
© 2018 Hogrefe Publishing. Nurses' inherently stressful occupation leaves them at a higher risk of developing negative mental states (stress, anxiety, and depression). However, research examining the effect of negative mental states on these health professionals' cognitive performance is sparse. Thus, the present study aimed to assess the link between negative mental states and cognitive performance in nurses (n = 53). Negative mental state data was obtained using the Depression Anxiety Stress Scale, brain activity was measured using electroencephalography, and finally, cognitive performance was assessed using the Cognistat and the Mini-Mental State Examination. Significant negative correlations (p <.05) were observed between anxiety and attention, and all three negative mental states and memory performance. Electroencephalographic changes indicated that increases in anxiety were significantly associated (p <.05) with decreases in gamma reactivity at fronto-central sites. The current study suggests that higher levels of negative mental states are associated with domain-specific cognitive impairments, and variations in gamma reactivity; possibly reflecting less optimal cortical functioning.
Maharaj, S, Lees, T & Lal, S 2019, 'Prevalence and Risk Factors of Depression, Anxiety, and Stress in a Cohort of Australian Nurses', International Journal of Environmental Research and Public Health, vol. 16, no. 1, pp. 1-10.View/Download from: UTS OPUS or Publisher's site
Nurses remain at the forefront of patient care. However, their heavy workload as a career can leave them overworked and stressed. The demanding nature of the occupation exposes nurses to a higher risk of developing negative mental states such as depression, anxiety, and stress. Hence, the current study aimed to assess the prevalence and risk factors of these mental states in a representative sample of Australian nurses. The Depression Anxiety Stress Scale was administered to 102 nurses. Information about demographic and work characteristics were obtained using lifestyle and in-house designed questionnaires. Prevalence rates of depression, anxiety, and stress were found to be 32.4%, 41.2%, and 41.2% respectively. Binominal logistic regressions for depression and stress were significant (p = 0.007, p = 0.009). Job dissatisfaction significantly predicted a higher risk of nurses developing symptoms of depression and stress respectively (p = 0.009, p = 0.011). Poor mental health among nurses may not only be detrimental to the individual but may also hinder professional performance and in turn, the quality of patient care provided. Further research in the area is required to identify support strategies and interventions that may improve the health and wellbeing of nursing professionals and hence the quality of care delivered.
Lees, T, Elliott, JL, Gunning, S, Newton, PJ, Rai, T & Lal, S 2019, 'A systematic review of the current evidence regarding interventions for anxiety, PTSD, sleepiness and fatigue in the law enforcement workplace.', Industrial health.View/Download from: Publisher's site
Law enforcement is inherently stressful, and police officers are particularly vulnerable to mental and physical disorders. As such, researchers are currently assessing intervention strategies that may combat or manage these psychological, physical and mental issues. To review most recent information regarding anxiety, PTSD, and sleepiness and fatigue and identify the interventions and treatments proposed to overcome work related stressors and associated mental illnesses inflicting law enforcement officers. The EMBASE, OVID MEDLINE and PsycINFO databases were canvassed for articles investigating anxiety, post-traumatic stress disorder, sleepiness, and fatigue. Initial article selections were made based on title, whilst final inclusion was informed by a full critical appraisal with respect to the primary and secondary effects. The systematic search returned 363 records, of which 183 were unique. Following screening, 43 records were included in the final review. The included literature assessed the efficacy of several interventions, and provided a number of recommendations regarding interventions, and policy. Moreover, literature indicates that police officers benefit from interventions targeting work-related stress and potential psychological disorders, if these interventions are continuous. Furthermore, larger controlled studies are required to further elucidate the benefits of psychosocial intervention in law enforcement.
Lees, T, Chalmers, T, Burton, D, Zilberg, E, Penzel, T, Lal, S & Lal, S 2018, 'Electroencephalography as a predictor of self-report fatigue/sleepiness during monotonous driving in train drivers.', Physiological measurement, vol. 39, no. 10, pp. 105012-105012.View/Download from: UTS OPUS or Publisher's site
OBJECTIVE:In this study, electroencephalography activity recorded during monotonous driving was investigated to examine the predictive capability of monopolar EEG analysis for fatigue/sleepiness in a cohort of train drivers. APPROACH:Sixty-three train drivers participated in the study, where 32- lead monopolar EEG data was recorded during a monotonous driving task. Participant sleepiness was assessed using the Pittsburgh sleep quality index (PSQI), the Epworth sleepiness scale (ESS), the Karolinksa sleepiness scale (KSS) and the checklist of individual strength 20 (CIS20). MAIN RESULTS:Self-reported fatigue/sleepiness scores of the train driver cohort were primarily associated with EEG delta, theta, and alpha variables; however, some beta and gamma associations were also implicated. Furthermore, general linear models informed by these EEG variables were able to predict self-reported scores with varying degrees of success, representing between 48% and 54% of variance in fatigue scores. SIGNIFICANCE:Self-reported fatigue/sleepiness scores of train drivers were predicted with varying degrees of success (dependent upon the self-reported fatigue/sleepiness measure) by alterations to monopolar delta, theta, and alpha band activity variables, indicating EEG as a potential indicator for fatigue/sleepiness in train drivers.
Lees, T, Fatima-Shad, K, Simpson, A, Nassif, N, Lin, Y & Lal, S 2018, 'Heart Rate Variability as a Biomarker for Predicting Stroke, Post-stroke Complications and Functionality', Biomarker Insights, vol. 13, pp. 1-13.View/Download from: UTS OPUS or Publisher's site
Background: Heart rate variability (HRV) is a non-invasive measure of the function of the autonomic nervous system, and its dynamic nature may provide a means through which stroke and its associated complications may be predicted, monitored, and managed.
Objective: The objective of this review is to identify and provide a critique on the most recent uses of HRV in stroke diagnosis/management and highlight areas that warrant further research.
Methods: The MEDLINE, CINAHL, and OVID MEDLINE databases were canvassed using a systematic search strategy, for articles investigating the use of HRV in stroke diagnosis and management. Initial paper selections were based on title alone, and final paper inclusion was informed by a full-text critical appraisal.
Results: The systematic search returned 98 records, of which 51 were unique. Following screening, 22 records were included in the final systematic review. The included papers provided some information regarding predicting incident stroke, which largely seems to be best predicted by time- and frequency-domain HRV parameters. Furthermore, post-stroke complications and functionality are similarly predicted by time- and frequency-domain parameters, as well as non-linear parameters in some instances.
Conclusions: Current research provides good evidence that HRV parameters may have utility as a biomarker for stroke and for post-stroke complications and/or functionality. Future research would benefit from the integration of non-linear, and novel parameters, the hybridisation of HRV parameters, and the expansion of the utilisation of predictive regression and hazard modelling.
Nurses function inside a particularly stressful occupation that requires the provision of continuous care to individuals who are often in great need. Stress has been shown to impair performance and specifically shown to impair nursing quality. However, we do not yet know how stress influences the cognitive performance of nurses, and hence, the present study investigated the associations between stress and cognitive performance in nurses using electroencephalography and administered cognitive assessments. Thirty-six nurses (34 women) of mean age 37.77±11.40years were recruited. Stress was examined using the Lifestyle Appraisal Questionnaire. Broad spectrum electroencephalogram activity at positions Fp1, Fp2, C3 and C4 was recorded for a 5-min baseline and active phase to physiologically assess cognitive performance. Additionally, the Mini-Mental State Exam and Cognistat were also used to measure cognitive performance. Assessed cognitive performance was not associated to stress, however, lifestyle factors, as well as a number of the examined cognitive electroencephalographic variables including changes in theta, alpha activity and gamma reactivity were. Definitively determining how stress affects the cognitive performance of nurses requires additional research; the present study forms a foundation from which future research can further expand the examination of stress exposure in nurses. Copyright © 2016 John Wiley & Sons, Ltd.
Lees, T, Nassif, N, Simpson, A, Shad-Kaneez, F, Martiniello-Wilks, R, Lin, Y, Jones, A, Qu, X & Lal, S 2017, 'Recent advances in molecular biomarkers for diabetes mellitus: a systematic review.', Biomarkers, vol. 22, no. 7, pp. 604-613.View/Download from: UTS OPUS or Publisher's site
CONTEXT: Diabetes is a growing global metabolic epidemic. Current research is focussing on exploring how the biological processes and clinical outcomes of diabetes are related and developing novel biomarkers to measure these relationships, as this can subsequently improve diagnostic, therapeutic and management capacity. OBJECTIVE: The objective of this study is to identify the most recent advances in molecular biomarkers of diabetes and directions that warrant further research. METHODS: Using a systematic search strategy, the MEDLINE, CINAHL and OVID MEDLINE databases were canvassed for articles that investigated molecular biomarkers for diabetes. Initial selections were made based on article title, whilst final inclusion was informed by a critical appraisal of the full text of each article. RESULTS: The systematic search returned 246 records, of which 113 were unique. Following screening, 29 records were included in the final review. Three main research strategies (the development of novel technologies, broad biomarker panels, and targeted approaches) identified a number of potential biomarkers for diabetes including miR-126, C-reactive protein, 2-aminoadipic acid and betatrophin. CONCLUSION: The most promising research avenue identified is the detection and quantification of micro RNA. Further, the utilisation of functionalised electrodes as a means to detect biomarker compounds also warrants attention.
Rothberg, LJ, Lees, T, Clifton-Bligh, R & Lal, S 2016, 'Association Between Heart Rate Variability Measures and Blood Glucose Levels: Implications for Noninvasive Glucose Monitoring for Diabetes', DIABETES TECHNOLOGY & THERAPEUTICS, vol. 18, no. 6, pp. 366-376.View/Download from: Publisher's site
Kalatzis, G, Lees, T, Nassif, N, Zaslawski, C & Lal, S 2017, 'Exploring cognitive function in diabetes and non-diabetes samples using electroencephalography (EEG) and psychometric assessment: a comparative study', 37th Annual Scientific Meeting of the Australasian Neuroscience Society.View/Download from: UTS OPUS
Kalatzis, G, Lees, T, Nassif, N, Zaslawski, C & Lal, S 2016, 'Investigating cognitive function in diabetes and healthy samples using electroencephalography (EEG) and psychometric assessment: a comparative study.', Inter-University Neuroscience & Mental Health Conference.View/Download from: UTS OPUS
Ty, L, Shamona, M & Sara, L 2015, 'Electroencephalographic markers of subjective cognitive performance: implications towards electrophysiological prediction of early cognitive decline', Frontiers in Human Neuroscience.View/Download from: Publisher's site
Lees, T, Kalatzis, G & Lal, S 2015, 'EXAMINING NEGATIVE MENTAL STATES AND THEIR ASSOCIATION TO PSYCHOMETRIC AND ELECTROENCEPHALOGRAPHIC MEASURES OF COGNITIVE PERFORMANCE IN AUSTRALIAN NURSES', PSYCHOPHYSIOLOGY, pp. S24-S24.
Elliott, J, Lees, T, Nassif, N & Lal, S 2015, 'Stress and the New South Wales Police Force: The prevalence of various coping mechanisms', Inter-University Neuroscience and Mental Health Conference.View/Download from: UTS OPUS
Vine, M, Lees, T, Nassif, N, Simpson, A & Lal, S 2017, 'Investigating the associations between ADHD symptomology and chronic illness: cardiovascular disease and diabetes mellitus'.View/Download from: UTS OPUS
Invited presentation given at the Warfighter Effectiveness Research Centre (WERC), United States Airforce Academy in 2015
Invited presentation given at the Warfighter Effectiveness Research Centre (WERC), United States Airforce Academy in 2015