Sleepy drivers have problems with keeping the vehicle within the lines, and might often need to apply a sudden or hard corrective steering wheel movement. Such movements, if they occur while driving on a slippery road, might increase the risk of ending off road due to the unforgiving nature of slippery roads. We tested this hypothesis. Twelve young men participated in a driving simulator experiment with two counterbalanced conditions; dry versus slippery road x day (alert) versus night (sleepy) driving. The participants drove 52.5 km on a monotonous two-lane highway and rated their sleepiness seven times using the Karolinska Sleepiness Scale. Blink durations were extracted from an electrooculogram. The standard deviation of lateral position and the smoothness of steering events were measures of driving performance. Each outcome variable was analysed with mixed-effect models with road condition, time-of-day and time-on-task as predictors. The Karolinska Sleepiness Scale increased with time-on-task (p < 0.001) and was higher during night drives (p < 0.001), with a three-way interaction suggesting a small increased sleepiness with driving time at night with slippery road conditions (p = 0.012). Blink durations increased with time-on-task (p < 0.01) with an interaction between time-of-day and road condition (p = 0.040) such that physiological sleepiness was lower for sleep-deprived participants in demanding road conditions. The standard deviation of lateral position increased with time-on-task (p = 0.026); however, during night driving it was lower on a slippery road (p = 0.025). The results indicate that driving in demanding road condition (i.e. slippery road) might further exhaust already sleepy drivers, although this is not clearly reflected in driving performance.

Ability tilt refers to a within-individual difference between two abilities (X-Y), e.g. differences between tech and verbal or verbal and math abilities. Studies have found associations between ability tilts and their constituent abilities (X or Y). Here we show that such associations may be spurious due to the non-independence of the two measures. Using data from the 1997 National Longitudinal Survey of Youth (NLSY97), we find that associations between ability and ability tilt may simply be due to more positive associations between two measures of the same or similar abilities compared to two measures of different or dissimilar abilities. This finding calls into question theoretical interpretations that have proposed that ability tilt correlations are due to differential investment of time and effort in one ability at the expense of the other ability.

Introduction: Body mass index (BMI) is a composite variable of weight and height, often used as a predictor of health outcomes, including mortality. The main purpose of combining weight and height in one variable is to obtain a measure of obesity independent of height. It is however unclear how accurate BMI is as a predictor of mortality compared with models including both weight and height or a weight x height interaction as predictors.

Methods: The current study used conscription data on weight, height, and BMI of Swedish men (N = 48,904) in 1969/70 as well as linked data on mortality (3442 deaths) between 1969 and 2008. Cox proportional hazard models including combinations of weight, height, and BMI at conscription as predictors of subsequent all-cause and cause-specific mortality were fitted to data.

Results: An increase by one standard deviation on weight and BMI were associated with an increase in hazard for all-cause mortality by 5.4% and 11.5%, respectively, while an increase by one standard deviation on height was associated with a decrease in hazard for all-cause mortality by 9.4%. The best-fitting model indicated lowest predicted all-cause mortality for those who weighed 60.5 kg at conscription, regardless of height. Further analyses of cause-specific mortality suggest that this weight seems to be a compromise between lower optimal weights to avoid cancer and CVD mortality and a higher optimal weight to not die by suicide.

Conclusions: According to the present findings, there are several ways to make better use of measured weight and height than to calculate BMI when predicting mortality.

Cognitive functioning is known to be impaired following sleep deprivation and to fluctuate depending on the time of day. However, most methods of assessing cognitive performance remain impractical for environments outside of the lab. This study investigated whether 2-min smartphone-based versions of commonly used cognitive tests could be used to assess the effects of sleep deprivation and time of day on diverse cognitive functions. After three nights of normal sleep, participants (N = 182) were randomised to either one night of sleep deprivation or a fourth night of normal sleep. Using the Karolinska WakeApp (KWA), participants completed a battery of 2-min cognitive tests, including measures of attention, arithmetic ability, episodic memory, working memory, and a Stroop test for cognitive conflict and behavioural adjustment. A baseline measurement was completed at 22:30 h, followed by three measurements the following day at approximately 08:00 h, 12:30 h, and 16:30 h. Sleep deprivation led to performance impairments in attention, arithmetic ability, episodic memory, and working memory. No effect of sleep deprivation was observed in the Stroop test. There were variations in attention and arithmetic test performance across different times of day. The effect of sleep deprivation on all cognitive tests was also found to vary at different times of day. In conclusion, this study shows that the KWA's 2-min cognitive tests can be used to detect cognitive impairments following sleep deprivation, and fluctuations in cognitive performance relating to time of day. The results demonstrate the potential of using brief smartphone-based tasks to measure a variety of cognitive abilities within sleep and fatigue research.

Objective: The present simulation study aimed to assess positive predictive value (PPV) and negative predictive value (NPV) for our newly introduced Accounting for Expected Adjusted Effect test (AEAE test) and compare it to PPV and NPV for a traditional zero-order. significance test.

Results: The AEAE test exhibited greater PPV compared to a traditional zero-order significance test, especially with a strong true adjusted effect, low prior probability, high degree of confounding, large sample size, high reliability in the measurement of predictor X and outcome Y, and low reliability in the measurement of confounder Z. The zero-order significance test, on the other hand, exhibited higher NPV, except for some combinations of high degree of confounding and large sample size, or low reliability in the measurement of Z and high reliability in the measurement of X/Y, in which case the zero-order significance test can be completely uninformative. Taken together, the findings demonstrate desirable statistical properties for the AEAE test compared to a traditional zero-order significance test.

The point that adjustment for confounders do not always guarantee protection against spurious findings and type 1-errors has been made before. The present simulation study indicates that for traditional regression methods, this risk is accentuated by a large sample size, low reliability in the measurement of the confounder, and high reliability in the measurement of the predictor and the outcome. However, this risk might be attenuated by calculating the expected adjusted effect, or the required reliability in the measurement of the possible confounder, with equations presented in the present paper.

Pain is subjective and largely shaped by context, yet, little is known about the boundaries for such influences, in particular in relation to conscious awareness. Here, we investigated processing of noxious stimuli during sleep. Four experiments were performed where participants (n = 114) were exposed to repetitions of noxious heat, either when awake or during sleep. A test-phase followed where participants were awake and exposed to painful stimuli and asked to rate pain. Two control experiments included only the test-phase, without any prior pain exposures. Participants in the awake condition rated all test-phase stimuli the same. Conversely, participants who had been sleeping, and thus unaware of getting noxious heat, displayed heightened pain during the first part of the test-phase. This heightened reaction to noxious stimuli-a pain alarm response-was further pronounced in the control conditions where participants were naive to noxious heat. Results suggest that the pain alarm response is partly dependent on conscious awareness.

According to the intelligence-creativity threshold hypothesis, there should be a positive association between intelligence and creative potential up to a certain point, the threshold, after which a further increase in intelligence should have no association with creativity. In the present simulation study, the measured intelligence and creativity of virtual subjects were affected by their true abilities as well as a disturbance factor that varied in magnitude between subjects. The results indicate that the hypothesized threshold-like association could be due to some disturbing factor, for example, low motivation, illness, or linguistic confusion, that varies between individuals and that affects both measured intelligence and measured creativity, especially if the actual association between intelligence and creativity is weak. This, together with previous negative findings, calls the validity of the intelligence-creativity threshold hypothesis into question.

P-hacking can be described as a more or less deliberate, explorative approach to data analysis with a flexible/opportunistic search space and the reporting of primarily statistically significant findings. This leads to inflated type-1 error rates and to bias in reported estimates in the scientific literature.

This thesis aims to describe how p-hacking can be manifested in academic research and to illustrate how bias due to p-hacking is expected to affect the veracity of published findings using two specific examples from the literature. This thesis also argues that when evaluating published findings in the current academic environment, we should assume a priori that biases due to p-hacking and publication bias are present.

The thesis used Monte Carlo simulations and systematic reviews of the literature in two specific fields: the proposed associations between exposure to night work and breast cancer in women, and between job strain and coronary heart disease.

A general model and mathematical framework to predict expected bias from p-hacking was developed, and can be used for  a priori defined protected inferences of any published finding, under explicit assumptions of various levels of p-hacking. The model indicated a close to 100% chance of demonstrating a false positive association in larger studies, but also showed that even minimal p-hacking results in substantial bias in estimates.

The literature review identified large flexibility in the analytical process, allowing for the final model to be picked from a large pool of available models, with an implied search space of thousands of estimates. Some of the specific observations made here could be used to argue evidence for high risk of p-hacking and publication bias in the reviewed literature:

• None of the 17 reviewed studies on job strain and coronary heart disease reported the proper estimate of the job strain interaction (chapter 6) and our analysis showed that the proper estimate would not have been statistically significant in any of the studies (chapter 7).
• One study described a data driven approach with an implied search space of at least 502 models, where adjusting for confounding did not reduce the strength of the association, as would be expected, but instead increased its strength so it fell above the threshold for statistical significance (chapter 5).
• One study was based on a speculative and marginally significant estimate after arbitrarily restricting the analysis to a subgroup, when estimates on the full group were available and indicated a non-significant association (chapter 5).
• Statistical power analyses on research into night work and breast cancer indicated that statistically significant findings were over-represented in the literature (p≈.001) suggesting the presence of bias from p-hacking or selective publishing of significant findings (chapter 5).

The findings also suggest that previously reported estimates in meta-analyses was likely to represent prevailing bias in the two fields reviewed here. A bias-adjusted meta-analysis on the job strain model and coronary heart disease with a total of 462,220 subjects and 6,836 CHD events indicated no support for the job strain interaction (RR=1.00; 95% CI: 0.88--1.14). In addition, it did not show an increased risk due to high job demand (RR=1.03; 95% CI: 0.97--1.11) but it did confirm previously reported risks due to low job control (RR=1.11; 95% CI: 1.03--1.20).

The pleiotropic cytokine interleukin-6 (IL-6) has been proposed to contribute to circadian regulation of sleepiness by increasing in the blood at night. Earlier studies have reported diurnal variation of IL-6, but phase estimates are conflicting. We have therefore performed a meta-analysis on the diurnal variation of circulating IL-6. Studies were included if they reported IL-6 in plasma or serum recorded at least twice within 24 hours in the same individual. A systematic search resulted in the inclusion of 43 studies with 56 datasets, for a total of 1100 participants. Individual participant data were available from 4 datasets with a total of 56 participants. Mixed-effects meta-regression modelling confirmed that IL-6 varied across the day, the most conspicuous effect being a trough in the morning. These results stand in contrast to earlier findings of a peak in the evening or night, and suggest that diurnal variation should be taken into account in order to avoid confounding by time of day in studies of IL-6 in plasma or serum.