Don’t Stand So Close To Me: Review

The study of psychology has been questioned to be an authentic study of science. However, the deciding factor of psychology being called “science” is not simply whether it matches a certain definition, but how the psychology is analyzed. Members of Georgetown University’s psychology department Joana B. Vieira and Abigail A. Marsh conducted a scientific experiment that addressed psychopathy and the regulation of interpersonal distance. They tested preferred interpersonal distance as it relates to psychopathic traits, specifically that of callousness, or cold-heartedness. Their thesis revolves around the amygdala function, and how lesions in the amygdala can cause an organism to react differently to interpersonal distance. Cited in the article are studies of amygdala on both humans and monkeys. This research aligns with amygdala dysfunction in psychopathic patients, and a new research question was contrived to add to this prior knowledge.

The experimenters make a clear connection to the amygdala dysfunction to interpersonal distance but decide to take it a step further by measuring psychopathic traits as well. They used a system called the Psychopathic Personality Inventory-Revised (PPI-R) to measure the psychopathic trait of cold-heartedness in the participants. Since prior research supports cold-heartedness to amygdala activity, they hypothesized that PPI-R Cold-heartedness scores would predict one’s preference of interpersonal distance. The experiment was a combination of administering this test, and a task allowing subjects to choose their preference of distance.

Forty-six participants were tested, each one receiving 32 trials that were divided into two blocks, Experimenter-walking and Participant-walking. For each block, there were four variables: eye contact/no eye contact, approach/withdrawal (approach trials were started at a distance and withdrawal trials were started up close). When the participant felt satisfied with the distance he would stop and the distance between his and the experimenter’s chin would be measured. It is important to note that the experimenter kept a neutral face and showed no signs of uneasiness to the experimenter, like previous experiments measuring psychopathy. When analyzing their data, they found that PPI-R scores for Cold-heartedness were significantly associated with interpersonal distance preferences (higher scores preferred lower distance).

This article was not only in line with previous scientific knowledge, but it added to that knowledge. No previous article has explored the relationship between psychopathic traits and interpersonal distance. However, the scientists used many prior research studies that helped them make claims in order to conduct their experiment smoothly. They referenced a previous experiment led by Daniel P. Kennedy that addressed personal space and the amygdala function, but took it a step further in adding a new variable: cold-heartedness PPI-R scores, a trait of psychopathy. In their data analysis, they were careful with certain interfering biases, like sex and cultural background. In their conclusion, they suggested ways to take the study further, therefore encouraging other scientists to develop their experiment the way they did with previous studies.

In short, this article explored the relationship between preferred interpersonal distances between cold-heartedness, a common trait in psychopathic individuals. The experiment was well thought out and implicated, and accounted for cultural and gender biases. This form of psychological study and data analysis is in fact a science, with many doors opening to more concentrated experiments.

Literature Cited

Vieira JB and Marsh AA (2014) Don’t stand so close to me: psychopathy and the regulation of interpersonal distance. Front. Hum. Neurosci. 7:907. doi: 10.3389/fnhum.2013.00907

The Left-Handed Advantage in Tennis

About 10 percent of the population holds an advantage when it comes to fighting situations and competitive sports: lefties. Left-handed individuals are rare in both the animal kingdom and the human population, so physical and strategic advantages allow lefties to benefit in one-on-one fighting situations. In a recent study published by Florian Loffing et al. in PLoS ONE journal, left-handed individuals, predominantly men, have the upper hand in tennis matches, although the advantage diminishes with higher performance levels. Although the article was an interesting read, the conclusions were rather obvious and were repeated several times throughout the article, as if the reiteration revealed new information.

Loffing and friends held two studies: left-handed professional and amateur tennis players. The study of professional tennis players was based on data published publicly online from 1973 to 2011. Analysis of data revealed an excess of left-handed professionals in 15 of the 39 years, with an inverse U-shaped curve peaking around the 1990s. Women were overrepresented only in 1981. Data for both studies were obtained from free online resources, searches on the web, or material voluntarily provided by tennis clubs in the WTV, in which 184 of the 597 tennis clubs responded. The online sources may be skeptical and loaded with misinformation. Additionally, the tennis clubs voluntarily responded, which introduces bias since the clubs with left-handed players would most likely respond.

Left-handed players were previously the highest ranked and best players in year-end rankings, but that advantage has decreased over time, which is obvious since professional players are accustomed to playing with left-handed players and spend an adequate amount of time to practice, prepare, and watch videos and read game statistics on their left-handed opponents.

Left-handed advantage in professional tennis is moderate in men’s competition and almost non-existent in females. The study exposes new information regarding left-handedness and sex, although it is revealed that this information was previously known, where “work on laterality effects in male and female sporting professionals found handedness to be performance-relevant in male rather than female competition” (Loffing 2). However, the data does not provide reasons or an explanation for this occurrence. Although it may be biological, it is not supported by the data obtained from this specific experiment.

Loffing et al. used information from a large survey administered to people ages 18-30, a range near the age range of professionals, and asked for handedness in both writing and throwing. This information was compared to left-handedness in tennis to determine the probability of finding more or an equal number of left-handed professionals by chance. The use of a survey introduces bias into the study, since it is only voluntary, and would most likely attract sports-oriented people. Secondly, throwing left-handed cannot be compared to playing left-handed in tennis. The motions differ significantly because the tennis swing requires technique and precise movement, and there is also the element of cross-dominance in handedness.

Despite the flaws in the study, it revealed new information on left-handed tennis players, a topic in which there is little research. The scientists were detailed with the source of their information, the calculations, and the significance of data and results obtained. The study was not an experiment per se, but more of a compilation of data already provided to the world. However, data was missing from certain years and from women’s tennis in general. The study provides a correlation between left-handed players and success in tennis, but only before the player reaches a professional level and becomes accustomed to left-handed players.

Citation:

Loffing F, Hagemann N, Strauss B (2012) Left-Handedness in Professional and Amateur Tennis. PLos ONE 7(11): e49325. doi:10.1371/journal.pone.0049325

Comparing Experiments to Models: Vibrating Guitar Strings

“An experimental analysis of a vibrating guitar string using high-speed photography,” by Scott B. Whitfield and Kurt B. Flesch of the University of Wisconsin – Eau Claire seeks to compare the waveform of a plucked string with a standard wave model of this vibration at various initial amplitudes and locations along the string. Whitfield and Flesch conclude that the experimental vibration matches well with the model when the string is plucked at small amplitudes. This detailed but relatively clear article contributes to physics due to its novelty and solid experimental design.

The method that Whitfield and Flesch used in order to make these comparisons is fairly simple, but is quite effective. First, they constructed a quasi-guitar using only one string and wooden boards (in order to enhance the visibility of the string). Next, they set up the remainder of the experiment, and then plucked the string at three separate locations: the middle of the string, 1/3 of the way from the string’s end, and 1/5 of the way from the string’s end. At each location, they made three plucks, each one at separate heights. When the string was plucked, they captured the string vibration using high-speed cameras and a computer program. Once they had captured the data, they compared the vibrating string to the model using both equations and the recorded images as an overlay on the model.

From this experiment, they were able to determine that the experimental pluck aligns most the model at smaller amplitudes, regardless of the location of the pluck. They also determined that at larger initial amplitudes, the experimental vibration strayed more from the modeled vibration. They argue that the string’s construction, including its material and tightness, had a greater effect on the larger plucks, which is why there is more variance from the model.

While this article could have explained its use of the equations slightly more, it was wholly clear and comprehensible. It also contributes heavily to the field, breaking new ground. No studies that compare a vibrating string to a standard wave model had been published prior to this one. This study is solid because it is consistent with previous knowledge (it cites Arthur Benade’s use of equations). But, while the data supports the conclusions drawn, Whitfield and Flesch made several assumptions regarding the decay of the strings and the string’s curve at the initial amplitude. They acknowledge these assumptions in their writing, but the effects that they assumed were negligible perhaps could have had an effect on the experimental vibration.

Thus, Whitfield and Flesch’s study concludes that, after comparing an experimental string’s vibration to a standard wave model, the vibrations most match at smaller initial amplitudes. This study is clear and definitely breaks new ground, which is what makes it good for physicists studying vibrating strings.

References
Whitfield, Scott B., Flesch, Kurt B. (2014). .An experimental analysis of a vibrating guitar string using high-speed photography. American Journal of Physics, 82; doi: 10.1119/1.4832195

A Deeper Understanding of Deforestation

This peer-reviewed article is the “Annual Carbon Emission from Deforestation” published in the journal PLoS ONE on May 2015. The article states that the current methods of assessing the carbon emissions from deforestation are inconsistent and are not done frequently enough to be valuable. The authors argue that deforestation has high variability, and that its rate can be estimated better by understanding the different annual trends and that neighboring areas can have vastly differing trends. Finding this trend is key into understanding and quantifying the deforestation rates and these trends can help deforestation mitigation programs target locations more accurately. Through its data collection method and its analysis, this article provides deeper insight into deforestation and carbon emissions. It also demonstrates the use of the annual trends and how this work can be improved in the future.

The article is based on research done to compare the deforestation rate to the carbon emission rate in the Amazon Basin. This data was collected using time-series satellite data from Landsat satellites and the Moderate-Resolution Imaging Spectroradiometer Vegetation Continuous Fields (MODIS VCF) over the span of 10 years. The datasets were separated into yearly intervals. The study found that carbon emission rates from deforestation differ not only from region to region, but also from year to year. The author argues that this is more accurate than past studies that were done by the United Nations’ (UN) Food and Agriculture Organization (FAO) every 5 or 10 years and it relied on each country’s reporting of forest cover change. Deforestation has also invaded into forests of high carbon density, meaning that there will be more carbon emission per deforested area. Since low carbon density forests have been cut down during the study period, the author closes stating that the remaining forest cover and its carbon density has to continue to be monitored in order to accurately estimate carbon changes in the future.

As the article stated, deforestation has become a major source of carbon dioxide released into the atmosphere. Due to this we should keep a better record of this and analyze the effects of deforestation more deeply. Now that deforestation has hit areas of high biomass, the emission rate will increase if left unattended. Since 2008, the forests cleared in Brazil, Peru, and Colombia has had a higher carbon density that the forests cleared prior to that year, meaning that the annual trend of emissions will increase. This trend is also important because it is a quantitative value that can be used by deforestation mitigation programs, such as UN’s Reducing Emissions from Deforestation and Forest Degradation (REDD+). This study can be useful to those that are looking to perform a similar study in their area. Programs like REDD+ can use this data to chose which locations are in need of their ecosystem services the most.

With the MODIS VCF technology improving, datasets can be reduced into monthly intervals to produce more accurate trends. Now that emission rates are known to vary from one region to another, there can be more precise studies can be made, not only of the Amazons, but also of other areas of the world. This gives more insight into pinpointing forests that are in dire need of protection.

References

Song, X., Huang, C., Saatchi, S. S., Hansen, M. C., & Townshend, J. R. (2015). Annual Carbon Emissions from Deforestation in the Amazon Basin between 2000 and 2010. Plos ONE, 10(5), 1-21. doi:10.1371/journal.pone.0126754