The use of red light cameras is a growing method of law enforcement over the past decade. The high speed cameras take a photo of drivers running red lights. A ticket is then mailed to the residence of the person to which the car is registered. These
cameras have come under attack in the U.S. Opponents of the cameras claim they are unconstitutional because they bypass due process. Proponents of the cameras claim they make the roadways safer. Since this is a class based on science, and not constitutional law, I was curious to the accuracy of the latter argument.

Red light cameras have two hypothesis that need to be tested. The first is that red light cameras cause a reduction in accident rates. The second hypothesis is that red light cameras cause a reduction in injuries and fatalities.

An observational study conducted by the IIHS rejected the null hypothesis that red light cameras do not reduce injuries and fatalities. Their study look at 99 U.S. cities around the country with a population of over 200,000 people. Of those 99 cities, 14 implemented red light camera enforcement. The IIHS observed accident data from those cities from 1992-1996 (when no cities used red light cameras) and from 2004-2008 (when 14 cities used red light cameras). The IIHS then analyzed “the citywide per capita rate of fatal red light running crashes…” Researches than did a statistical analysis and found that fatal red light running fatal crashes declined by 35% compared to 14% in other cities. The IIHS then estimated, after controlling for land area and population density, the IIHS estimates that the fatal rate of accidents due to red light running in 2004-2008 was reduced by 24%.

There are a few problems with this study. The first is the sample size. Only about 14% of the cities evaluated had red light cameras in use. That is disproportionate to the number of cities without the cameras. The results of the individual cities with cameras have a greater affect on the analysis because there are so few in the camera category (similar to the kids and e-ciggarette study Andrew showed us). Also, although third variables stated to measured, it is impossible to account for all confounding variables in this kind of study. Population type could be a factor for example. According to a Washington Post article, people in the Millennial Generation are driving less than previous generations. Therefore, there were more teen drivers in proportion to the population in 1992-1996 than there are from 2004-2008. Teen drivers are more likely to take risks behind the wheel, and with their diminishing driving habits, there is reason to believe this could have affected the study.

Another, more thorough, observational study published in the Journal of Safety Research found data consistent with the null hypothesis that red light cameras reduce accident rates. The study evaluated 253 signalized intersections in Flanders, Belgium from 2002-2007. During that time period, red light cameras were installed, and researches evaluated the effects. The study displayed a complex statistical method for controlling for trend effects (trends in related injuries in Flanders). Then, researches did a meta-analysis of all the intersections in the study. They found the following:

“The analyses showed a non-significant increase of 5% in the number of injury crashes. An almost significant decrease of 14% was found for the more severe crashes. The number of rear-end crashes turned out to have increased significantly (+ 44%), whereas a non-significant decrease (− 6%) was found in the number of side crashes. The decrease for the severe crashes was mainly attributable to the effect on side crashes, for which a significant decrease of 24% was found.”

This study is well conducted. It has a large sample size, and takes into account trend affects. It fails to reject the null hypothesis that red light cameras reduce accident rates. It does, however, support the the alternative hypothesis that red light cameras reduce severe accidents resulting in fatalities or serious injuries. There could be compounding variables though. For example, in the five year span from 2002-2007, automotive crashworthiness likely improved. The implementation of side airbags became more common in new cars during that time period, which may have affected the rate of serious accidents. Also, the narrow scope in regard to the location may not represent a worldwide or an American population.

I would like to see a thorough observational study conducted that looks at cities’ past insurance claims, crash data, population density, population demographics etc. From there, the chosen, similar cities would be randomly required to implement red light camera enforcement. The study would last only a year to limit the effect of technological advances in automotive safety. From this study, a better conclusion could be made with regard to the hypothesis proposed.

In a 1982 issue of The Atlantic, a renowned theory was published. It was the broken window theory. The theory basically states that if a building has a broken window, vandals will likely break the other windows and/or break into the building. The article theorizes that small, petty crimes lead to a culture of disorder and crime; therefore, small, often victimless crimes should be prosecuted with “zero tolerance” policies to reduce petty crimes and reduce major crimes. I wonder if there were any studies that support or reject this theory.

Many proponents of this theory point to New York City during the 90’s. William J. Bratton was appointed police commissioner, and he developed a “zero tolerance for graffiti and turnstile-jumping.” During this time, violent crime fell by 51% and homicides fell by 72%. his seems to back the hypothesis that a zero tolerance for petty crimes decreases major felonies, but correlation does not equal causation. I was immediately susceptible to confounding variables. It could also be reverse causation. Could violent crime cause more smaller, petty crimes?

A study conducted by the University of Chicago Law Review proposed the decline of the violent crime rate was largely due to the decline in the crack epidemic in America. Evaluating the different precincts in the city supported this hypothesis. Their study found that “those precincts that received the most intensive broken windows policing are the ones with the largest increases and levels of crime during the city’s crack epidemic. Consistent with findings elsewhere from city-level data, 99 jurisdictions with the greatest increases in crime during this period tend to experience the largest subsequent declines as well.” By looking at the individual precincts of law enforcement in the city, this study is able to show how confounding variables, not the zero tolerance policy, was the cause for a decrease in crime.

Testing this theory is very difficult. In a perfect world, I would like to see experiments set up. Random cities would be chosen, and each city would be randomly instructed to adopt or not adopt zero tolerance policies for small crimes. If enough cities and towns were involved in the study, and allocation of enforcement type was random, reasonable evidence should arise to support or reject the alternative hypothesis. This experiment should also be conducted at the same time to attempt the elimination of third variables. A third variable that may be time sensitive could be seen during the 90’s, when crime went down in virtually every city, not just NYC, due to the decline in crack.

The broken window theory is a popular theory for discussion, but there is little evidence to support or reject both the null and alternative hypothesis. Even the creator of the theory, James Q. Wilson states, “I still to this day do not know if improving order will or will not reduce crime. People have not understood that this was a speculation.”

Growing up, I was forced to wear a bike helmet by my parents and the law. In Pennsylvania, kids under the age of twelve must wear helmets. The reasoning behind wearing a helmet is to reduce risk of head injury in the event of an accident, but like many people, however, I have a distaste for helmets because it ruins my hair. I rarely ride my bike around campus
, and I probably will not commute via
bike to my future job, but I do see the increasing trend in metropolitan areas. Because of this trend, I wonder if regulators will implement mandatory helmet laws and if those laws would improve or reduce safety.

Last year a leading neurosurgeon, Dr. Henry Marsh, made controversial comments with regard to bicycle helmets. He stated that people using helmets are wasting their time, and that the helmets are “too flimsy” to do any help. Dr. Marsh uses anecdotal evidence to back his claim by referring to patients of his whose helmets did not protect them. He goes on to mention the fact that he has been riding for about 40 years and never has only been knocked off his bike once and without major injury.

Dr. Marsh’s comments are anecdotal observations and do not have any observational or experimental studies in support of his observations. However, because of his medical prestige, his opinion is valued more by the public and newspaper publications. This is all too common in the media. A report is made about an opinion of a doctor or a scholar, and the general public reads it at face value and believes it.

Although Dr. Marsh’s were not convincing to me, there was a study conducted by Ian Walker, a professor at the University of Bath, which found that bicyclists wearing helmets encountered riskier automotive maneuvers in their vicinity than non-helmet wearing bicyclists. Walker mounted several ultrasonic sensors on himself and his bike while he was riding. Over the course of two months, Walker rode his bike with and without his helmet. During that time span, 2,355 vehicles overtook him, and he found that on average, vehicles passed him about 3.5 inches closer when he was wearing a helmet. Walker hypothesizes that drivers are more cautious around people not wearing helmets. Walker’s study seems well down. It has a large sample size. He does, however,  ride on multiple different street types (one-way, two way, those with bike lanes, etc.) which might interfere with testing the alternative hypothesis that wearing bike helmets alone cause cars to pass closer. Walker also measured curb distance he was riding, the type of car passing (i.e. truck, bus, car, etc.), the color of the car, the time of day, etc. All these measurements may lead to a Texas sharpshooter problem. A correlation is bound to arise with all of these measurements.

Upon re-analysis of this study however, Professor Jake Olivier, a statistician, disputes Walker’s findings. Olivier first points out that the average passing of a vehicle was over a
meter in length. Therefore, Olivier re-analyzed the data according to “the recommended one metre rule into close (less than 1 m) and far (greater than or equal to 1 m) [passing] distances.” After crunching the numbers Olivier found that there is no significant difference to passing buffer distance given to Walker when he was or was not wearing a helmet. This re-analyses gives important insight to this theory. It shows that the deviation between average passing space by c
ars when Walker was and was not wearing a helmet is not significantly different.

Furthermore, a meta-analysis of bike injuries published in Accident Analysis and Prevention found that helmets significantly reduce risk of injury if an accident occurs. The analysis found risk “reduction estimates of at least 45% for head injury, 33% for brain injury, 27% for facial injury and 29% for fatal injury.” The meta-analysis was conducted the best it could be. There is now experimentally designed studies with regard to injury, and many of the studies included evaluated children’s injuries while my main inquiry was with regard to adults. A file drawer problem is suggested because most of the studies found helmets had a positive effect of reducing risk of injury. However, of the 63 studies, 7 did not find a positive effe
ct, which suggest that a file drawer problem is not present because 9% of the studies failed to reject the null hypothesis.

Overall however, I am concerned about the data in the individual studies. Is it possible that risk taking is a confounding variable? People who take risks do not wear helmets and also take risks while riding. Or, do people who wear helmets have more confidence, herefore, take more risks. As of now, the evidence on the topic is not very convincing either way. I would be hard to conduct any blind experiment because the cyclist and other auto traffic know if he/she is wearing a helmet. I guess the best study would be observational of bike crashes, measuring many third variables and limiting the study to only adult riders in metropolitan areas.

The acquisition of material possessions is inherent to American culture. Ideally in this country, anyone that works hard and captures various opportunities can excel economically, and what better way is there to show the world you made it than buying a huge house, luxury car, and a solid gold toilet? But, does working solely to buy more nice things (i.e. materialism) lead to satisfaction in life?

The first study I came across was an observational study conducted by Tim Kasser. To conduct this study, Kasser created a questionnaire, “The Aspiration Index,” measuring people’s valuation of certain goals. That questionnaire, along with four other questionnaires that “assessed positive feelings of well-being and negative feelings of distress,” were distributed to 316 students at the University of Rochester. He then used statistical analyses “to examine how people’s value orientations related to their well-being.” The analyses revealed a direct correlation with materialism, depression, and anxiety. This first study of Kasser’s has an ample sample size of 316, but he did not specify if his distribution was random. If the questionnaires were give to a specific group of people, it may not accurately represent the population has a whole. Also, since this was an observational study, reverse causation cannot be ruled out. If someone is depressed, it seems possible that he/she might think material possessions could make them happier. Likewise, if someone suffers from anxiety, valuing and having nice things could reduce symptoms. Furthermore, there are many possible confounding variables that are not accounted for. For example, the actions of the parents of the college children. If the parents of the child were materialistic, they might have focused more on making money than about the well being of the child. This causes the child to be depressed and he or she has materialistic tendencies because his or her parents do.

Kasser went further with the study, however. Instead of college students, Kasser observed adults in Rochester. He randomly chose 100 adults, ages 18-79, in Rochester and gave the the same questionnaires. The results were in accordance to his first study; Materialism, depression, and anxiety are directly correlated. Although this study was random, a sample size of 100 is quite small, and it still does not answer my concerns about confounding variables and reverse causation. Also, are people living in Rochester, NY an accurate representation of all humanity? Probably not. However, Kasser does go on however to state that similar studies in other countries reveal similar findings.

In his paper, Kasser also discusses many other studies that reveal the same positive correlation between materialism and low well-being. Therefore, an important contribution of this debate is a meta-analysis. Newell Wright of Western Carolina University and Val Larsen of Virginia Polytechnic Institute and State University conducted a meta-analysis on the issue. There meta-analysis, Materialism and Life Satisfaction, “examined the materialism/satisfaction relationship. It shows that the negative correlation between these variables is consistent across all studies.” It seems that this meta-analysis further supports the hypothesis that materialism causes a lower well-being, but the meta-analysis poses the possibility that this hypothesis is a victim of confirmation bias and the file drawer problem. The studies’ results may conflict with the scientists ideology. If the scientists believe in socialism and social equality, they will be more keen on finding and publishing results that support their ideology. It is more news worthy to publish a study that denounces materialism, a sort of status quo in America. Also, the study could influence public opinion about political policy. Likewise, if any of their results found a correlation between materialism and higher well-being, they could be left in the file drawer, never to be published because it goes against their ideology and political agenda. Furthermore, the meta-analysts stated that there were, in fact, a handful of studies that studied positive effects of materialism and found a direct correlation. Since there apparently are several studies about the positive effects, I am led to believe even further that this hypothesis falls victim to the file drawer problem.

Studying the affects of materialism on well-being is very difficult because there is no way to conduct an experiment. Scientists can not simply manipulate the materialistic personalities of a human being to study the hypothesis that materialism causes a lower well-being. At this point there have been only properly replicated observations in regard to this hypothesis. Although these observations consistently reject the null hypothesis, a file drawer problem seems to be present. I would like to see more studies on the matter that do an effective job ruling out reverse causation and confounding variables.

An earlier post of mine described how appropriate speed limits are set and why it is important to reduce speed variation within traffic, but I did not effectively present the argument as to why this is important.

An observational study conducted by AAA Foundation for Traffic Safety over the course of 4 years. The study chose 36 locations to conduct their study. These locations included rural interstates, urban interstates, and
fre
eways/expressways. The researchers chose sites that are similar to each other, to limit confounding variables, and that had adequate accident data, adequate exposure data, and that were easy to collect new data. Since the study was conducted  over the course of four years, it is reasonable to assume that the sample size is large enough. This study observed a direct correlation between speed variance and accident rate. However, one of my concerns with this study is that it uses past accident data from the Virginia Department of Transportation and present, collected data with regard to drivers speed. Therefore, the accidents rates used in the study are of events in the past, and the speed data was collected at a later time. There could be a difference of speed variance over that time. Also, the location of sites is limited to only Virginian roads. Much of the country, such as the mid west and west, has a different topography that may affect drivers visibility and road patterns, which may affect speed. Also, there is a cultural driving difference in different regions. For example, New England drivers are notorious for their fast and aggressive driving. It would like to see similar studies in different regions.

The AAA study concluded that speed variance would best be minimized when speed limits were set 5-10 mph below the design speed of the roadway. Their conclusion is backed by the mathematical models they developed from their data. This conclusion seems idealistic because it was substantiated on mathematical models. Usually, what may seem practical and logical on paper does not play out in reality, especially when humans are involved. The study does a good job observing the relationship between speed variance and accident rate. However, I wanted to see other studies that focused on the best way to reduce speed variation.

Another study conducted by the Michigan State Police addresses speed limits and speed variance in a more realistic way. They conducted a test on the same highway that had speed zones of both 55mph and 70mph. Their study found that in the 55 mph zones, the average speed was 66.4 mph and a variance of 36.1 mph. On the contrary, in the 70 mph zone had an average speed was 67.7 mph and variance of 27.8 mph, a 33% decrease. Also, outliers also decreased in this study. In the 55 mph zone 2.1% of drivers exceeded 80 mph while only 1.1% exceeded 80 mph in the 70 mph zone. This study though was quite short and it was done for different amounts of time in each speed zone. In the 55 mph zone, data was only collected for 17 minutes, but in the 70 mph zone, the data was only collected 18 minutes. Therefore, only 658 cars’ speeds were recorded in the 55 mph zone compared to 721 cars in the 70 mph zone. The study did not also specify the time of day that the it was conducted. Although the study sheds light on the matter and limiting speed variance by setting speed limits at the 85th percentile, there are flaws with the observational study. More studies should be conducted for a longer period of time, in several different states, and at similar time of day to determine the best speed limiting speed variance.

This study also refutes opponents arguments against adjusting speed limits to the 85th percentile. The Insurance Institute for Highway Safety (IIHS) website state, “The 85th percentile is not a stationary point. It is, rather, a moving target that increases when speed limits are raised. If speed limits are raised to meet a current 85th percentile speed, a new, higher 85th percentile speed will likely result.” Average speed increasing with the speed limit as hypothesized by this statement is not backed by any scientific studies.  The study discussed earlier conducted by the Michigan State Police is evidence that rejects this alternative hypothesis. The null hypothesis, raising speed limits will not raise average speed, is either correct or a false positive according to the Michigan study. Like I mentioned before, the difference in average speed in the 70 mph zone was only 1.3 mph faster than in the 55 mph zone.

The IIHS also states on there website to combat raising speed limits to the 85th percentile by stating how about 10,000 automotive deaths were due to speed-related incidents.  They conveniently kept that statistic ambiguous to make the consumer of their website think that statistic only accounts for speeding above the posted limit. What the IIHS failed to mention about the National Highway Traffic Safety Administrations (NHTSA) statistics that they cited is the numerous confounding variables contribute to the the “speed-related” fatalities. The confounding variables are included in the very definition of a speed-related crash, which is defined as, “any crash in which the police indicate that one or more drivers involved was exceeding the posted speed limit, driving too fast for conditions, driving at a speed greater than reasonable or prudent, exceeding a special speed limit or zone, or racing.” It also states a disclaimer that , “there is a significant overlap between alcohol involvement and speed. Many speed-related crashes involved alcohol and vice-versa.” This was purposefully not mentioned on the IIHS website because it would weaken their argument. For example, a 2007 NHTSA report stated, “In 2007, 40 percent of drivers with a BAC of .08 g/dL or higher involved in fatal crashes were speeding, compared with only 15 percent of drivers with a BACof.00g/ dL involved in fatal crashes.” Although this is a statistic from 2007, 2013 should not differ by much. Therefore, it is common for a speed-related crash to also be an alcohol-related crash.

After delving into the studies and statistics even deeper than before, I am convinced that speed variance is more of a threat to road safety than speeding. I am lead to believe by the Michigan State Police that the most appropriate speed limit should be the 85th percentile, but I would like to see more extensive studies with similar conclusions.

Andrew mentioned that a likely area of increased scientific research in the near future will be in regard to symptoms and whether to treat them or not. For example, when I would get a blister, my father would always insist on puncturing the blister and cutting the dead skin.  His reasoning was that it would allow new skin to regrow at a quicker rate. Seems logical, so I followed his advice, but now I am having doubts about his advice and wonder if it would be better to let my skin heal uninterrupted.

histology of a blister

The first pertaining study I found was an experiment was published in the Journal of the American Medical Association. The study was well conducted experiment. It used 83 volunteers (72 active duty servicemen and 6 male civilians and 3 female civilians) and administered about 300 friction blisters amongst the volunteers. All the blisters were administered in the same fashion. A mechanical pencil eraser was pressed down on the skin and “briskly rotated in a counter-clockwise direction.” The location of the administered blisters was also consistent. All but four blisters were “produced on the hypothenar eminences of both palms.” The other four were placed on heels of the volunteers.

To evaluate different methods of treatment, the scientist conducted the study by randomly chosing blisters of the soldiers (the civilians blisters were used for histology) to leave undrained, blisters to be drained, and blisters to be deroofed. By randomly choosing the blisters for each category, the study eliminates any externalities or confounding variables. One of my concerns was the consistency of the blister administration. It is unlikely that any human could exert the same force and movement with the eraser 300 times, but the randomization will eliminate that concern. The experiment concluded that draining the blisters either 3 times within the first 24 hours or 1 time between 24 and 72 hours allows for the quickest recovery time and least amount of pain.

Recovery time is important, (especially in the military) but I wonder about infectious risk when puncturing the blister to let it drain or deroofing it entirely. Luckily, a study in the British Medical Journal addresses my concerns. The study was observational and experimental, evaluating burn victims and their blister healing process. The study had 202 participants with similar wounds. The scientist chose individuals that “the extent of injury averaged 1% of body surface area; all burns except one were partial thickness and healed with conservative treatment. Only thermal burns of the arms and legs that could be treated with paraffin gauze dressings were included; most were of mixed depth. All residual sprays and ointments used in first aid were removed by washing with sterile saline.” Since the blisters were not administered by scientists, this part of the study is observational, but the treatment of the blisters was the experimental portion of the study. Participants’ blister(s) were randomly treated by leaving them intact, having them aspirated, or having them deroofed. The wounds were swabbed and “analyzed according to standard bacteriological methods.” The study results are in the table below.

The results of the study conclude that keeping a blister intact is the most effective method to limit infectious risk. Although the treatment method was randomized and that should eliminate any externalities, the blisters were not administered by scientists like study published in the Journal of the American Medical Association. That being said, the study is still convincing because the scientist observed and chose similar burn blisters to use in their expiriment of treatment.

Both of theses two studies used good sample sizes and randomization when experimenting with blister treatment. Neither study concluded that deroofing a blister, like my dad suggests, is a good idea. A person with a blister can make it heal faster by aspirating it of fluid, but that also increases the risk of infection. Blisters are generally not life-threatening, but these studies shed light on future physician approaches to the treatment of symptoms.

“When you work hard all day with your head and know you must work again the next day, what else can change your ideas and make them run in a different plane like whisky?”

—Ernest Hemingway

One of the things that I always found intriguing in my literature classes was the seemingly overwhelming number of writers that were supposed alcoholics. Whenever we discussed authors such as Ernest Hemingway, Edgar Allen Poe, Truman Capote, or F. Scott Fitzgerald, a discussion of their drinking habits always arose. This got me curious as to if there was any scientific cause behind alcohol and creativity. The fact that these renowned authors frequently drink is simply second hand, anecdotal evidence to the hypothesis that drinking increases creativity. Although this evidence is helpful, I wondered if any relative experiments were ever conducted.

The first experiment that was able to shed light on the subject is know as the Newt/Judge experiment. In this experiment, 18 marketing professionals were split into two teams of 9.”One team was plied with as much alcohol as they wanted, while the other team was assigned a liquid diet that the temperance movement would have approved of.” From there, the two teams were given a task to promote intermittent drinks of water at a bar/club. After three hours of collaboration, the teams handed in their proposals. The team allowed to drink developed 59 ideas in 3 hours while the sober team only proposed 48 ideas. The experiment shows that the inebriated team was more productive,  but were their ideas better? The five best ideas from each group were selected and put before a marketing director (who didn’t know whose ideas were whose) to rank. According to a marketing director, the ideas of the “boozer” team were better than the sober team. “The boozers came up with four out of the five top ideas,” concluded the study.

Furthermore, a more scientific study conducted by the University of Illinois had similar findings. The team of psychologist recruited “a target sample of 40 male social drinkers aged 21–30” through Craigslist and the university community. Of their sample, they randomly chose 20 of the subject to stay sober and the other 20 were given alcohol until they reached a BAC of about .075. The alcohol impairs “executive controls” of the intoxicated participants which the suspected causal link to more creative thought. of The psychologist then gave each participant a Remote Associates Test (RAT). According to the report, “The RAT is a commonly used creative problem solving task… participants are given three target words such as PEACH, ARM, and TAR, and are tasked with finding a fourth word, such as PIT, that forms a good two-word phrase with each of the target words. The RAT is thought to involve creative problem solving because the most salient potential responses to the problem are often incorrect, and one must retrieve more remote associates in order to reach solution.” The test basically assess the participants ability to link three words with one word. This is generally a good test because it can easily compare the sober and intoxicated participants. “If reduced executive control does in fact aid in creative problem solving, then participants in the intoxication condition should solve more RAT items than those in the sober control condition, or they may solve them more quickly.” The results revealed that the inebriated participants were more creative because they scored, on average, higher than the sober participants. The study concluded that “the results of the current study supported the prediction that moderate alcohol intoxication would improve performance on a creative problem solving task. Intoxicated participants not only showed an improvement in RAT accuracy compared to sober, WMC-matched participants, but they also solved problems more quickly.” It is suggested that because of alcohols impairment of “executive controls,” the intoxicated subjects did not fixate on a single idea. If a solution became too difficult, they sought an easier solution and found it quickly. 

Although these studies support the hypothesis that moderate intoxication increases creativity, there are many other health related risks that accompany frequent drinking. Many of the authors I previously mentioned suffered the consequences of drinking. For example, F. Scott Fitzgerald died of a heart attack at age 44 (about 18 years younger than the life expectancy of the time), and Ernest Hemingway committed suicide. The heavy drinking a suspected contributing factor to both of theses authors’  fates.

FLOOR IT?!

Over the summer I had the pleasure of taking a road trip to Houston, Texas to help move my older sister there for a co-op with Exxon Mobil. One of the stark difference about Texas is the topography. Living in Pittsburgh, there are hills everywhere, and as a result, the roads are quite curvy and the speed on most interstates is 65 mph. But, in Texas, everything is flat, and the majority of their interstates have speed limits of 75 mph or greater. This was very exciting considering that I have a lead foot. I did wonder, however, about the safety consequences of the increased speed limits, and if there was a causation between automotive accident rates and/or fatality rates and speed limits. I also wondered how speed limits are determined.

Texas Highway 130’s 85mph speed limit.

The issue of determining speed limits is a prominent issue in the United States especially with recent advancement in automotive technology. Adrian Lund, the president of the Insurance Institute of Highway Safety (IIHS), stated,”The cars now make you feel more comfortable when you are going 85, 95 or even 100 miles per hour. Ten years ago, when a car got up around 80 or 85 miles per hour, it did not handle as well and you didn’t feel as comfortable driving it.” There is a growing trend in states to raise speed limits, the current highest posted speed limit being Texas State Highway 130 at 85 mph, and many safety groups such as the IIHS are starkly opposed. They propose that the recent trends “in [the] 24 states that raised speed limits… [resulted in] 15 percent more fatalities on interstates and freeways than otherwise would have been expected.” The institute continues in their status report by stating, “Even with today’s speed limits, speed-related crashes cause more than 10,000 deaths a year — nearly a third of all crash fatalities in the country. States could prevent some of these deaths if, instead of giving drivers permission to go ever faster, they vigorously enforced existing limits to slow drivers down.”

However, many statistics they use are somewhat misleading. For example, speed-related crashes is a very broad category, and by investigating further, the National Highway Traffic Administration defines speed-relating accidents as “any crash in which the police indicate that one or more drivers involved was exceeding the posted speed limit, driving too fast for conditions, driving at a speed greater than reasonable or prudent, exceeding a special speed limit or zone, or racing.” Also, the federal agency states that “there is a significant overlap between alcohol involvement and speed…this same caveat applies to many of the other scenarios examined in this report, as multiple factors can be involved in any given crash.” From reading the actual report that the IIHS refers to, their statistical argument is diminished because there are many confounding variables which are conveniently  ignored.

The IIHS and proponents of lower speed limits will often point to 1974, the year the a national speed limit was set to 55mph. Although this was to combat the energy crisis, safety proponents exalted the fact that “the first year after the lower limits were in place, highway deaths plunged by 15 percent.” This fact was revealed as a fallacy when the CATO Institute unearthed that fatalities most likely declined as a result of the energy crisis itself. After all, “higher gas prices reduced driving by about 20 to 30 percent in many states.” The fatality rate likely fell because less people were driving.

Furthermore, a CATO Institute analysis of states’  speed limits provide evidence against the hypothesis that increasing speed limits increases accidents and fatalities. In 1995, the national government repealed national speed limit laws, returning sovereignty to the states. The analysis stated, “Although 33 states raised their speed limits between the 1995 repeal of the mandatory federal speed limit and August 1996, the National Highway Traffic Safety Administration reported last October that “the traffic death rate dropped to a record low level in 1997 (1.6 deaths per 100 million vehicle miles traveled).”

Determining a safe speed limit is largely based on statistics. The Michigan State Police Traffic Services Section determined that the safest speed is what 85% of people drive at or below. The report states that this speed, “provides the lowest speed variance between vehicles, and thus provides the lowest crash numbers.” Michigan State police argue that speed variance is the main problem not velocity. A common argument against this notion is that people will always exceed the limit posted. The IIHS states, “People often drive faster than the speed limit, and if the limit is raised they will go faster still.” But, Michigan State police disagree. In their report, they state how “travel speeds don’t change” when the posted speed limit increases or decreases. What changes is the public perception, and their perception does not align with reality which is why it is important to set speed limits that limit speed variation.

When did I write this post? Spongebob knows.

When asked when my favorite time of the day is, I reply in a witty manner, at night.  I enjoy staying up late and frequently do so because my schedule allows it. (My earliest class is 12:20 pm and it’s only on Mondays.) do not know why, but I feel more energized at night. I often wonder why this is, and why other people enjoy the mornings.

Our diurnal preferences are suspected to be a result of genetic evolution. Dr. Mike Nichols states how “window of opportunity” for a rival tribe to attack in the predeceasing ages of humanity is diminished if “half the tribe were night owls and the other half early birds.” Thus, “having such a variety of chronotypes in a tribe would be very desirable.”

The Surrey Sleep Research Centre has found an association between diurnal preference and the PER3 gene. The 675 participants between the ages of 20 and 35 in the study were asked to complete a questionnaire “to assess sleep and psychological and health characteristics.” The participants were then genotyped for the PER3 VNTR (variable number tandem repeat) gene. As a result of the study, scientists concluded that “homozygosity for the longer allele (PER3(5/5)) of the VNTR was associated with increased morning preference, earlier wake time and bedtime, and reduced daytime sleepiness.” The scientists also state that “[the gene] may also modify the effects of sleep on health outcome measures.” But this is not as conclusive because the health questionnaire results do not reveal an association between the genotype and “physical or psychological characteristics.”

Another study conducted by geneticists at the University of Leicester used fruit flies to discover that “nearly 80 genes [are] associated with ‘morningness’ and ‘eveningness.'” How much in common do humans have with fruit flies was my first question, but according to the scientists, there is much we have in common.  Dr. Eran Tauber stated that “a relatively large number of genes were associated with a molecular signalling pathway called MAPK…genes that we identified are not core-clock genes, but genes involved in a diverse range of molecular pathways.”

This is an important finding because it reveals that there is more to our diurnal preference than just the PER3 gene. Dr. Tauber also added that in this modern time, many of us spend our life indoors which distorts the body’s ability to recognize the difference in light and temperature during the day and night. He goes on to state, “To make matters even worse, the rhythm of life is such that for many people the economic or social call to start a new day comes hours before the endogenous call from the body clock.” By experimenting with the fruit flies, Dr. Tauber states how “this changes our view of the body clock, from a pacemaker that drives rhythms to a time reference system that interacts with the environment.”

Are you and early bird or a night owl? And, what are supposed consequences of such tendencies? Comment and let me know what you find!

One of the many reasons why I am excited to be in college is the fact that I may be alone,  whenever I please, and not be deemed a social outcast. I am not anti-social, per se, and I can easily carry out a conversion with people. In fact, my job when I am at home is selling shoes on commission. Thus, my ability to interact with the customer is directly correlated to my income, and I do quite well. That being said however, I treasure my alone time. Most of you, like myself, understand the characteristics of an introvert and extrovert, but I am curious as to why people are introverts or extroverts. And, because I exhibit characteristics of both, is there something in between?

Right off the bat, I found that there is a middle ground, ambiversion. Ambiverts are sort of a forgotten personality type, yet many people fall into that category. Even Carl Jung, the psychologist that coined the term “introvert” and “extrovert”, stated, “There is no such thing as a pure introvert or extrovert. Such a person would be in the lunatic asylum.” (You have to love the lack of political correctness in the 1920’s.)

I am still however curious as to the cause of introverted or extroverted nature. One theory is that our “individual differences in dopamine promote variation in the heterosynaptic plasticity that enhances the connection between incentive context and incentive motivation and behavior.” In simple terms, extroverts’ brains’  have an increased activation of reward-sensastive areas when receiving awards. This theory is backed by the evidence found in the Cognitive Brain Research medical journal. The study “used functional magnetic resonance imaging (fMRI) to examine whether individual differences in extraversion predict the reactivity of the brain’s dopaminergic neural reward system.”

MRI image of extrovert brain activity (S7) compared to introvert brain activity (S13) when exposed to reward. (Image from study live link)

Based on the findings, the scientists involved stated that there are “clear links between stable individual differences in personality, genetics, and functioning of the brain’s reward system.”

While reading through the study myself, (most of which went right over my head) I did wonder about confounding variables. The human brain is incredibly complex, and there is still much we do not know about it. Could there possibly be a third variable that explains the direct correlation between extraversion and high brain activity when exposed to reward? The authors list several caveats to outlining possible problems with their study and things that might have skewed the results.

Do you find yourself to be more of an introvert, extrovert, or ambivert? And, do you think the brain activity of reward sensitive areas is the only explanation to your personality? Please, comment your thoughts/findings.

College is an incredible time to experience things for the first time. One of those experiences for me and probably many of you is living with a roommate. Even during orientation my roommate and I had a dispute regarding the temperature of the room. I for one enjoy a cooler room, especially when sleeping, but that is not the case for everyone and I am curious as to why. At first I had a few preliminary question such as, why we, as humans, are uncomfortable when the temperature of our surroundings is the temperature of our body (98.6 degrees fahrenheit). Simply put, our bodies’ metabolisms continuously generates heat, and if the temperature of our surroundings is the same as our bodies, it is difficult to expel heat and cool down.

the metabolic process

Our metabolisms are the main determination for room temperature preferences; having a higher metabolism equates to a cooler room preference. A difference in metabolic rate may cause a few issues especially in the office setting. Generally, the current office temperature is set to about 70 degrees fahrenheit, and that standard temperature exist due to the average metabolic rate of a 40 year old, 155 pound male which was the average office occupant in the 1930’s. As the role of woman in society has progressed and their presence in the office has increased, many woman find the temperature too cold. Men, as a whole, have a greater muscle to fat ratio than woman, and since muscle cells require more energy (and give off more heat) to operate than fat cells, woman consistently have a lower resting metabolism.

However, metabolism is not the sole explanation for room temperature preference. Much of it is psychological. Psychologist William C. Howell conducted an experiment regarding the human perception of temperature. His study concluded that as humans, we cannot physically distinguish temperature changes within a several degree variation. Much of our perception of temperature is based on social cues such as weather reports and advertisements.

Due to a higher presence of woman in the office, the average temperature of an office building may be increasing in the near future (although a few degrees difference in temperature cannot really be detected by humans) However, it was found office temperature does affect workers performance. One study conducted by the Lawrence Berkeley National Laboratory concluded that worker performance consistently decreases when the temperature rises above 24-26 degrees celsius (about 75-80 degrees fahrenheit).

I only skimmed the surface on how temperature affects us humans, and there are many more studies on this subject such as the healthiest temperature for our sleeping environment and how the temperature affects the body during exercise. Comment and tell me what temperature you all prefer and any other interesting findings that might relate.

Hello, I am Walt. I am delighted to figure that I already have something in common with all of you; none of us are pursuing a major or career in science. For me personally, science isn’t my thing because of my experiences in high school. They weren’t bad per se, (I surely am not scarred for life) but I am just not intrigued by the narrow focus that usually accompanies scientific research. I prefer the big picture which is why I loved my macroeconomics class in high school. Seeing everything mesh together and the theoretical cause and effects on different markets definitely clicked in my head; therefore, I intend to major in finance and someday I want to work in sales and trading on Wall St. For motivation, my desktop background is the world renowned Charging Bull on Broadway St. in New York, NY. (pictured below)

I took this class mainly because I need the gen ed credit. However, I chose SC 200 over other science classes because of Andrew’s rate my professor rating. Although previous students of Andrew did not say this was an easy class, they did say it was very interesting and it was highly recommended. Also, when searching for classes to take, I liked how the class description stressed critical thinking because that is an important skill in any industry, especially finance. I don’t want to waste time or money and  Andrew’s class is a science course that will provide me with a greater understanding of the world and the valuable skill of critical thinking.