Master of Science

thesisToday, the majority of people in the United States reside in dynamic urban environments and navigate multiple, complex situations in their daily routines. These factors of modern life often require prolonged appropriation of cognitive energy to both external stimuli and a continuous series of tasks, resulting in directed attention fatigue. Directed attention fatigue is marked by a diminishment in an individual’s physiological state (alterations in neural activity), cognitive state (a decrease in motivation, reduction in the capacity to focus attention, and difficulties ignoring irrelevant information), and affective state (changes in emotional responses). The depletion of this resource results in, among other things, reduced task performance, which carries a potential for drastic, negative consequences. Increasingly, mobile phones are having a significant impact on these states. As of 2013, an estimated 91% of adults owned a mobile phone and most frequently use it for texting. Emerging trends involve the changing relationship between user and device, as a growing number of smartphone owners exhibit behaviors of over-use, dependency, and even addiction. Given the near constant presence of mobile phones and their increasing use for personal and professional purposes, their ability to constantly place demands on directed attention is cause for concern. Exposure to nature-rich surroundings, however, has been shown to activate alternate attentional networks, forcing the deactivation and restoration of the directed attention network. It was the purpose of this pilot study to determine to what extent directed attention is activated or deactivated in a nature-based environment when an individual is aware of the potentially distracting presence of their mobile phone. To this end, electroencephalograph recordings, a Recognition Memory Task, and the Positive and Negative Affect Schedule were utilized, with and compared across two participant groups â€" those completing a nature walk without a phone and those completing it while receiving text messages on their phones (though instructed not to interact with the device). Upon processing the data, no significant differences were found to exist between groups. The pilot design of this study, however, has offered insight on previously unaccounted for variables, and has the potential to inform the development of future studies

Exposure to Radiofrequency Electromagnetic Fields and Sleep Quality: A Prospective Cohort Study

BACKGROUND: There is persistent public concern about sleep disturbances due to radiofrequency electromagnetic field (RF-EMF) exposure. The aim of this prospective cohort study was to investigate whether sleep quality is affected by mobile phone use or by other RF-EMF sources in the everyday environment. METHODS: We conducted a prospective cohort study with 955 study participants aged between 30 and 60 years. Sleep quality and daytime sleepiness was assessed by means of standardized questionnaires in May 2008 (baseline) and May 2009 (follow-up). We also asked about mobile and cordless phone use and asked study participants for consent to obtain their mobile phone connection data from the mobile phone operators. Exposure to environmental RF-EMF was computed for each study participant using a previously developed and validated prediction model. In a nested sample of 119 study participants, RF-EMF exposure was measured in the bedroom and data on sleep behavior was collected by means of actigraphy during two weeks. Data were analyzed using multivariable regression models adjusted for relevant confounders. RESULTS: In the longitudinal analyses neither operator-recorded nor self-reported mobile phone use was associated with sleep disturbances or daytime sleepiness. Also, exposure to environmental RF-EMF did not affect self-reported sleep quality. The results from the longitudinal analyses were confirmed in the nested sleep study with objectively recorded exposure and measured sleep behavior data. CONCLUSIONS: We did not find evidence for adverse effects on sleep quality from RF-EMF exposure in our everyday environmen

Effects of radiofrequency electromagnetic field exposure on sleep quality

The use of wireless communication devices, which emit radiofrequency electromagnetic fields (RF-EMF), has increased in the past decades. According to the World Health Organization (WHO) mobile phone use is ubiquitous with an estimated 4.6 billion subscriptions globally. The missing knowledge about a biological mechanism and the attribution of non-specific symptoms of ill health to RF-EMF has led to an increased public concern about possible adverse health effects from this radiation. One of the most often reported symptoms due to RF-EMF exposure are sleep disturbances. In several randomised double-blind human laboratory studies, changes in the sleep electroencephalogram (EEG) after exposure to RF-EMF were observed. The impact of these small changes on sleep quality and therefore on general well-being is unclear. Previous epidemiological studies have used a cross-sectional design, which is not appropriate for establishing causal relationships between exposure and outcome. Studies with a cohort design are therefore needed. Additionally, exposure assessment was mostly inadequate or only parts of the real exposure situation were taken into account. Personal measurement devices (exposimeters) have become available a few years age. In large epidemiological studies, it is very time-consuming and costly to use such devices. Other exposure assessment methods are therefore needed. The main aim of this thesis was to investigate the association between personal RF-EMF exposure and sleep quality by using objective as well as subjective data. To predict personal exposure to RF-EMF a comprehensive exposure assessment method was applied. This thesis was part of the QUALIFEX project (a prospective cohort study on radiofrequency electromagnetic field exposure and health related quality of life) which is embedded in the National Research Program 57 (NRP-57) about non-ionising radiation. The health effect of RF-EMF exposure was investigated in a cohort study which consisted of a baseline survey in May 2008 and a follow-up survey one year later. Questionnaires entitled „Environment and Health“ were sent out to 1375 randomly selected study participants in the region of Basel (Switzerland). Information on sleep quality, on exposure relevant factors and on various confounding factors was collected. By means of a pre-study, which was not part of this thesis, a comprehensive exposure assessment method was developed. To predict personal exposure to far-field RF-EMF (e.g mobile phone base stations or radio transmitters), a validated full exposure prediction model was used which was developed based personal exposure measurements of 166 study participants who took part in a pre-study. Exposure to close to body sources was assessed using self-reported data on mobile phone and cordless phone use. Objective data of mobile phone use from network operators for participants who gave informed consent were additionally collected. For a nested sleep study, 120 participants out of the baseline survey took part in a nested sleep study to verify our previous results. Sleep quality and sleep behavior was assessed using actigraphy and exposure to RF-EMF was measured by means of personal exposimeters. For the baseline survey, mean calculated RF-EMF exposure to all relevant sources of all 1375 study participants was 0.12 mW/m2 (0.21 V/m). Exposure at the follow-up survey was 0.13 mW/m2 (0.22 V/m) and therefore comparable with the baseline exposure. No consistent association between RF-EMF exposure and self-reported sleep quality neither in the baseline analysis (cross-sectional analysis) nor in the cohort analysis (longitudinal analysis) was observed. In the nested sleep study, objective data on exposure and sleep quality did not yield any association between exposure and sleep quality. The QUALIFEX project was the first study which applied a cohort design to investigate the association between RF-EMF exposure and sleep quality. Additionally, we were able to verify our results of the cohort study with objective data obtained in a nested sleep study. Overall, we found no consistent association between self-reported as well as objectively measured sleep quality and exposure to relevant RF-EMF sources in everyday life. Our results increase the evidence for a true absence of an effect of RF-EMF exposure on sleep quality. Our study used a very comprehensive exposure assessment method which included far-field sources as well as close to body sources. In general, exposure levels were very small and changes between the baseline and the follow-up survey were marginal. Hence, with our study no conclusions can be drawn regarding potential health effects of higher exposure levels. In future studies, more data on long-term effects have to be collected. Additionally, the exposure situation in everyday life should be monitored because new technologies operating with RF-EMF are continuously arising

Effects of mobile phone radiation on the human central nervous system

The effects of mobile phone-like electromagnetic radiation on the human brain activity are examined. The research focuses on both radio frequency (RF) exposures and the much less studied low frequency (ELF) exposures (less than 40 kHz) arising from the battery operation of GSM handsets. The first single blind study recruited a small sample of twelve human volunteers. The eyes closed resting EEG activity is monitored after radio frequency exposure. With SAR levels of 2 W/kg, results reveal no statistical changes in any of the examined frequency bands for neither pulsed modulated RF signals nor continuous wave RF signals. In the second double blind study, a sample of 72 volunteers is recruited and an improved protocol comprised of separate pulsed RF, continuous RF and pulsed ELF exposures is employed. Exposures are delivered through a custom made handset capable of independent RF and ELF exposures. Findings include a reduced alpha band frequency activity during pulsed radio frequency and low frequency radiations exposures but no changes under the continuous RF radiation. Changes are present both during as well as after exposure, while greater changes are observed during exposures. The study of some non linear measures of the resting EEG revealed no changes under any of the active exposures. As the observed changes are very close to the normal EEG variation during resting conditions, their biological significance and health impact is not immediately obvious. However, their mere demonstration points to a low level interaction mechanism which may deserve further study

Effects of Screen Light Filtering Software on Sleep and Morning Alertness

Research has shown that blue light can impact the circadian rhythm. Research has also suggested that use of electronic devices, such as computers and televisions that emit blue light before sleep, can negatively impact sleep quality. This research has led to the creation of computer software which lowers the levels of blue light in the evening to help with sleep. This study looked at the impact of wavelength filtering software on sleep onset, sleep duration and subjective alertness after morning waking of four college students. The college students were randomized into two groups and had the wavelength filtering software f.lux installed on their computer. Participants in the intervention group had their computer set to display 1900 K light 2 hours before bedtime for 7 days straight while the control group had their computer set to display 5000 K light. All participants were asked to complete the Pittsburgh Sleep Diary for 7 days straight. Participants in the 1900 K light condition on average had a longer sleep onset latency, shorter sleep duration and were subjectively less alert in the morning compared to the 5000 K light condition. However, the variability within groups made any differences in the means statistically insignificant. The majority of participants in both groups wanted to continue the software after the study. The low sample size prevented significant results from being formed. The study served as a pilot study to help direct future research on wavelength filtering software

Adolescents' electronic device use, sleep, and wellbeing

Many adolescents regularly use electronic devices, and a substantial proportion of adolescents use these devices in bed before they go to sleep. They are also at risk of using alcohol, recreational drugs, and tobacco, of becoming overweight or obese and having poor mental health. This thesis has investigated how adolescents' electronic device use affects their sleep and their wellbeing and examined (a) whether weekday and weekend sleep are explained using the same variables, (b) how device use affects sleep, and (c) how poor sleep affects mood. This thesis consists of three studies. Study 1 (N = 405) and study 2 (N = 489) both examined whether device use predicted poor and ill-timed sleep whilst simultaneously including other variables which are known to affect adolescents' sleep. Moreover, the studies also examined whether the factors which predicted weekday sleep also predicted weekend sleep. Thirdly, the studies examined the relationships between device use, sleep, and health related factors. The third study (N = 19) examined whether the blue light, content that was viewed on devices or the timing of device use affected adolescents' sleep and their following day mood. This thesis has shown that adolescents' weekday and weekend sleep are explained differently. Adolescents who were more anxious or were more aroused had poorer weekday sleep and adolescents who socialised more at the weekend had poorer weekend sleep. Importantly, the thesis has shown that more frequent device use, later use of electronic devices and using more interactive content predict poorer sleep quality and ill-timed sleep. Finally, this thesis has shown that poor and ill-timed sleep predicted worse mood. The findings from this thesis show that research should recognise that adolescents sleep differently on weekdays than they do at the weekend. The findings also show that researchers should investigate how the timing and content that individuals view on their electronic devices affects sleep

Wireless phone use by young New Zealanders: Health and policy implications

Over the last decade the use of cellphones has increased dramatically among the young adolescent population. In New Zealand, most children of this age also use a cordless phone. With the rapid proliferation in children‘s use of these devices, there has been increasing concern about whether children are more vulnerable than adults to possible adverse outcomes if such effects do result from wireless phone radiofrequency exposure. This is the first study of young New Zealanders‘ wireless phone habits, focusing particularly on the extent of use, and the relationship of that use with well-being. Two studies were undertaken: a census of schools with Year 7 and 8 classes in the Wellington Region of New Zealand to ascertain what rules were in place regarding cellphones at school, and a cross-sectional survey of students from the same region, using a representative sample of 373 students aged 10.3-13.7years. Both studies were conducted by the author independently from any research group. The primary research appears in Part II. Chapter 5 presents wireless phone user-habits. The large majority of young adolescents were already using cellphones and cordless phones regularly in 2009, although use was generally light or moderate. A small group (5%) was using both phone types extensively (≥ 30 minutes cordless daily plus ≥ 10 cellphone calls weekly); almost a quarter used a cordless phone ≥ 30 minutes daily, and 6% reported, on average, 1¼ hours or more use daily. This extent of use over 4 or more years has been associated in several major studies with an increased risk of glioma. Both the MoRPhEUS data and this study‘s data (Appendix 1 and Chapter 5) showed that use of the two phone types is positively correlated, increasing the comparative and actual radiofrequency exposure in heavy users. Cellphone use during school was compared with school expectations, discussed in chapter 6, showing there was a considerably greater level of illicit use than that of which principals were aware. This use was adjacent to the lower abdomen, and a brief review of relevant fertility literature suggested that cellphone use, or even carriage, in that position may impair sperm quality and duration of use like this appeared consistent with reduced fertility. A novel observation is explored in chapter 7. The mental process in recalling the extent of cellphone use was not linear. It parallels that found in many types of magnitude estimation, using a logarithmic mental number line. This carried implications for epidemiology methods that use recall data, particularly the need to record the geometric rather than arithmetic mean when a range of estimated use is provided. Not doing so put almost 5% of participants in an incorrect category when estimated use was split into tertiles. Recall estimation has a large variance. Chapter 8 presents a Bayesian method of reducing estimation bias in recall data. It should be applicable for use by studies that conform to the method‘s requirements. Chapter 9 presents the results of logistic regression analysis of the participants‘ reported well-being with respect to their wireless phone use. A dose-response relationship with frequent headaches confirmed findings elsewhere. Tinnitus and tiredness results suggested that responses were different depending upon phone type. This is the first study to explore and demonstrate different well-being responses according to cordless phone frequency or modulation. There was a strong association between being woken by the cellphone in the night and being tired at school. This research carries implications for young people‘s wireless phone use, including the advisability of limiting daily use to no more than 15 minutes daily. The relevance of researchers considering cellphone exposures, compared to that of cordless phones, is questioned. Further research on bio-sensitive frequencies, modulations and exposures is needed. An important recommendation is for the inclusion of education about wireless technology in schools and school communities and for child-health practitioners

Quantifying Quality of Life

Describes technological methods and tools for objective and quantitative assessment of QoL Appraises technology-enabled methods for incorporating QoL measurements in medicine Highlights the success factors for adoption and scaling of technology-enabled methods This open access book presents the rise of technology-enabled methods and tools for objective, quantitative assessment of Quality of Life (QoL), while following the WHOQOL model. It is an in-depth resource describing and examining state-of-the-art, minimally obtrusive, ubiquitous technologies. Highlighting the required factors for adoption and scaling of technology-enabled methods and tools for QoL assessment, it also describes how these technologies can be leveraged for behavior change, disease prevention, health management and long-term QoL enhancement in populations at large. Quantifying Quality of Life: Incorporating Daily Life into Medicine fills a gap in the field of QoL by providing assessment methods, techniques and tools. These assessments differ from the current methods that are now mostly infrequent, subjective, qualitative, memory-based, context-poor and sparse. Therefore, it is an ideal resource for physicians, physicians in training, software and hardware developers, computer scientists, data scientists, behavioural scientists, entrepreneurs, healthcare leaders and administrators who are seeking an up-to-date resource on this subject