For my TA – comments due by wednesday 18th april

• http://ellislee15.wordpress.com/2012/03/21/can-we-trust-an-eyewitness-testimony/#comment-71  (AWAITING MODERATION…)
• http://notwilliam.wordpress.com/2012/03/25/informed-consent/#comment-118
• http://psud60.wordpress.com/2012/03/25/psychological-trauma-within-soldiers-of-the-u-s-army/#comment-40 (AWAITING MODERATION…)
• http://psucc3.wordpress.com/2012/03/21/the-gender-bender/#comment-72

The stats of infidelity

This blog is a lot longer than my usual ones, but I thought this topic deserved it…
The issue of remaining faithful in a relationship is arguably one of the most important, and one which can make or break the relationship for obvious reasons.  The general well-known stereotype is that men cheat more than women, however I decided to look deeper into this because, although having been cheated on myself more than once, I have many male friends who describe girls doing the same to them.  So is the original stereotype true?  Do men cheat more than women?  Is it in fact the other way around, and women cheat more than men do?  Or are both men and women equally as unfaithful?  So I will look at this stereotype; why it may exist and whether research has found it to be true or not, while also taking into consideration factors which may affect a person’s faithfulness.

A proposed possible explanation for the stereotype of men cheating more than women do is because of the existing opinion that they have an innate sexual behaviour, and that modern Western culture goes against this which causes them to cheat more.  This is claimed by Eric Anderson, an American sociologist.  According to him, after a maximum of 2 years men would become sexually bored with partners and so look for new experiences.  He claims that religion and social conventions stop many people from doing what simply comes naturally.  I don’t know about you, but to me this seems like a ridiculous form of an excuse for men to go ‘Yeah, see that’s why I cheat!  I can’t help it, it’s natural!’ which in some eyes may give a ludicrous ‘way out’ for those who are unfaithful.  However, while we’re looking at the innate biological side of things, I’ll point out that it is of a well and widely-received opinion that male humans (like many male animal species) are hard-wired to want to spread their genes as far out as possible, while women (like many female animal species) search for a mate to settle down with and help raise offspring.  This could be an explanation as to why men would cheat more, and can also be seen in the animal kingdom with many examples of one male who has a herd, pride or group of many females (for example horses, lions, cows, etc).  However, there are also those animals who mate for life and remain faithful, such as swans, gibbons and even certain types of fish.  So for those who claim that multiple partners is an innate, biological, animal instinct – and we are essentially animals therefore follow this – it is simply untrue.

Another possible explanation that men would cheat more than women follows this argument: it has been shown that on average, men want sex more than women; a social psychologist in Florida State University, Roy Baumeister, states that “men want sex more often than women at the start of a relationship, in the middle of it, and after many years of it.”  Also supporting this, it can be seen in everyday life that there are a lot more female prostitutes and sex workers, and also, rather shockingly, research has shown that nuns are far better at keeping their chastity vows than priests!  This all obviously suggests that men need more sex, and more often, which will inevitably lead to more cases of them cheating.

There are many aspects surrounding the whole issue of infidelity which may be contributing factors, such as whether or not you’re in a happy relationship to start with.  Research has shown (and it’s just plain common sense) that men and women who are in good relationships cheat less; Brand, Markey, Mills & Hodges (2007) found that women reported one reason for cheating as being unhappy in the current relationship.
Another, rather surprising, possible factor may lie in an individual’s genes.  A study of 552 sets of twins found that men who carried a certain gene variant were much more likely to have had serious relationship problems in the past year than those men who didn’t carry the gene variant.  This variance in their genetic make-up doesn’t necessarily mean that these individuals *were* unfaithful, but common sense – and research evidence – means that if you’re having problems in your relationship, you’re more likely to be unfaithful (see above regarding people cheating more when in an unhappy relationship).
More research has shown that other possible contributing factors to infidelity may be certain characteristics of individuals, for example one study which found that men who worry about their sexual performances are actually more likely to be unfaithful to their partners, which to me is rather surprising!  Added to this, another study found that men were more likely to stray if they were financially dependent on their other halves.  Perhaps the feelings of inadequacy in terms of money spur men on to try and make up for it with sexual encounters.

So now onto the part I’m sure you’ve all been waiting for…  Who does research tell us cheats more?  Is it men or is it women?  Well here it is folks: it’s the blokes, but not by much!  Recent research indicates that the gap is narrowing fast between the number of men who cheat vs the number of women who cheat, with a Dutch study last year finding that out of over 1000 people, 22% of the men admitted to cheating and 19% of the women did too.  Although yes, there is the possibility that some people may have lied and not admitted to it, this would have been the same for both sexes, and the point is that the figures are nearly equal.  These similar numbers for men and women are backed up by another 2011 study published in the Psychological Science journal, which found that gender made no difference in the numbers of individuals in positions of power who had cheated in the past or had a desire to be unfaithful in the future.  This can be explained by the opinion of Joris Lammers, a psychologist at Tilburg University, that “as more and more women are in greater positions of power and are considered equal to men, then familiar assumptions about their behaviour may also change.”
However, for all you fellas out there feeling hard done by with these findings, Brand, Markey, Mills & Hodges (2007) actually found that in their study, ‘women reported being as unfaithful or more unfaithful than men.’  According to them, men were also more suspicious about cheating, and also more likely to discover the cheating than women were.

So what can we say from all this?  Well it looks like the stereotype of men cheating more than women do is backed up by findings from research studies, although there are also studies which claim that women cheat just as much as, if not on an equal level with, men.  So it’s all basically pretty even.  However, I would like to finish this last blog of the semester on a more positive note 🙂  If 20% of men are said to have cheated, this means that 80% remain faithful!  Good news!  So for those of you out there who worry about your other half straying, relax, it’s actually not as common as we all think (regardless of how often it appears on Jeremy Kyle).  It also looks like the best way to remain faithful is to be in a happy relationship, which is what we all aim for anyway, so in the words of George Michael, ‘you gotta have faith’ that your partner is one of the faithful 80%.

 

 

 

References (like an idiot I closed most of the tabs which had the papers on them, but here’s 2 if you’re interested.  There’s also links to other relevant papers on the left-hand-side of the first reference here):

• Brand, Markey, Mills and Hodges (2007) — http://www.springerlink.com/content/9326845m6234776h/
• Wilson (2012) — http://him.uk.msn.com/sex-and-dating/are-men-hardwired-to-cheat

For my TA – comments due by wednesday 14th march

• http://statsisboring.wordpress.com/2011/10/07/do-you-need-statistics-to-understand-your-data/#comment-57
• http://emu2468.wordpress.com/2012/03/11/is-it-possible-for-a-researcher-to-be-truly-objective-when-conducting-their-experiments/#comment-69
• http://psucc3.wordpress.com/2012/03/07/what-you-wear-defines-you-as-a-person/#comment-68
• http://thought3.wordpress.com/2012/03/11/listening-to-mozart-reduces-allergic-skin-wheal-responses/#comment-60

Bias in Research

Psychologists and also the general public a lot of the time rely on research findings to make decisions on varying things such as theories and even their own health.  The worrying thing is that in some cases, these findings are either not entirely true or perhaps hiding the truth, which inevitably will mislead people and therefore cause decisions to be made which will be based on untrue ‘facts’.  One of the main causes for results being hidden or altered is bias in the research; the companies which fund the research a lot of the time would benefit from positive findings.  Therefore they might either purposefully pressure researchers or in some cases alter or hide results to make their product look better and therefore sell more.

One such example of bias in research is with a drug called paroxetine (or Paxil) which is an anti-anxiety medicine.  Results from four of the trials on this drug were suppressed, results which not only failed to show effectiveness of the drug among children and teens, but also which demonstrated a possible increased risk of suicidal tendencies.  The company which suppressed these results, GlaxoSmithKline, were forced to make a legal settlement which meant that they have now established an online registry which shows summaries of all the results of their sponsored studies which have happened after a certain date.  But the fact is that they suppressed results of trials in the first place, just to make their product look better and in the process not telling the public the possible risks.  This example shows possibly one of the worst dangers of bias in research, that people may die simply because results were suppressed.

So what can be done to combat this?  There are steps being taken: for example in June 2009, the FDA’s (Food and Drug Administration) Transparency Task Force was launched, which last year proposed draft plans that would make information about drugs and medical devices much more publicly available.
Although there is this progress, bias in research is still a real issue.  Without funding, there wouldn’t be nearly as much research actually completed, however if companies continue to fund research on their own products, bias will continue to occur.  It’s a sticky business with a lot of issues, so what are your views?

For my TA – comments due by wednesday 22nd february

• http://thewonderfulworldofstats.wordpress.com/2012/02/16/the-whole-truth-and-nothing-but-the-truth-when-journalists-report-research/#comment-27
• http://ruthtanti.wordpress.com/2012/02/19/sem-2-3-autism-statistics/#comment-63
• http://psychosomething.wordpress.com/2012/02/19/crazy-cat-lady-can-she-be-helped/#comment-39
• http://notwilliam.wordpress.com/2012/02/20/obsrvational-psychology/#comment-96

Can correlation show causality?

Ahhh yes, the age-old stats question…. to which I shall now give my view and explain why I have this view.
If, like me, you have always been taught that ‘correlation DOES NOT MEAN causation’ , you are not alone!  In my opinion this statement is correct, and I’ll explain why I think this is later on.

But the question in the title of this blog is whether or not correlation can show causality.  Which, in my opinion, it can.  I’ll explain why now…  Take an example, with 2 variables, where a set of results show positive correlation.  Looking at a graph, this is what it would look like.

This graph shows a positive correlation, I’m sure you would all agree.  Let’s assume that in this example, the 2 variables have causation.  In other words, the variable represented on the bottom of the graph (let’s call it variable 1, original I know) directly affects the variable represented on the side of the graph (variable 2).  The positive correlation shown in the graph demonstrates that the 2 variables both increase in number together; as variable 1 gets bigger, so does variable 2.  Therefore it can be said that this positive correlation has illustrated – or shown – the causality.
However!  I’m going to emphasize that in this example, the relationship between the 2 variables was already there, but that the positive correlation helped to show the causality….. I hope you understand this!

So now I shall make my point that although correlation can show causality, it DOES NOT MEAN causality.  Just because 2 variables are positively correlated, it does not necessarily mean that one causes the other to occur.  There may be other reasons for the correlation, for example a third variable which affects both.
Let’s take the same graph as before.

Again, you can see the positive correlation.  Now, what if I told you that in this example, the variable along the x axis (along the bottom) represented the number of shark attacks during the year, and the variable along the y axis (up the side) represented the number of ice cream sales during the year?  Yes, both numbers increase (as it heads to summer).  So they are positively correlated.  BUT one is not causing the other!  You don’t see people after being attacked by a shark think, “oh, I’d like an ice cream now…”  Maybe a silly example but you get my point.

In case you got lost in all that, what I’m saying is that I completely agree with what we’ve been brought up being taught, and that just because there is a correlation between 2 or more variables, it does not mean that there is causation.  However, as explained above (or attempted to explain!) positive correlation can show (or illustrate) a causality between variables.

For my TA – comments due by wednesday 8th february

• http://frasersstatsblog.wordpress.com/2012/02/05/can-alcohol-improve-your-revision/#comment-50
• http://psychosomething.wordpress.com/2012/02/05/my-super-sweet-16-child-abuse-on-television/#comment-26
• http://ishanichakravorty.wordpress.com/2012/02/05/should-psychology-be-written-for-laymen-or-scientists/#comment-35
• http://statisticsbyrachel.wordpress.com/2012/02/05/moral-justification-and-ethical-issues-with-non-human-animals/#comment-54

The stats of Valentine’s Day

Yes folks, a new year, a new set of blogs….  And since it’s approaching that time of year (Valentine’s Day), I thought I’d write about that 🙂

The typical feelings about Valentine’s Day varies depending on whether you are male or female, single or in a relationship, and for obvious reasons.  The stereotypes are that women expect to be pampered, men are expected to go all out doing the pampering and those not in a relationship spend the day either moping around or proudly proclaiming their independence.  As a girl myself, I would expect my fella to make some kind of effort!  But I’m also ashamed to admit that until now I haven’t given much thought as to how much pressure this puts on the guys…. is there actual evidence that on one specific day, men can feel more pressure than women?  If there *is* this pressure, do men tend to dread Valentine’s Day?  This also got me wondering what reasons people have to give presents; if they feel so stressed, why would they want to give presents at all?  So this is what I’ll be looking at 🙂

Otnes, Ruth and Milbourne (1994) did a qualitative study which focused solely on the male perspective of Valentine’s Day, as previous studies had focused on womens’.  They found that men do feel as if there is a negative pressure to participate in Valentine’s Day, but also that they enjoy giving gifts to their significant others despite this.  This to me is cute; blokes putting in the effort despite feeling the pressure to!  It’s also reassuring that they appear to enjoy spoiling us ladies.
However, a pilot study by Goodwin, Smith and Spiggle (1990) made me a tad concerned….  They found that ‘consumers tend to define gift giving as obligatory or voluntary, and [also] that this distinction affects their gift selection process and post-purchase behaviors.’  Basically, depending on whether people want to give gifts just because, or whether they feel that they have to – for a certain holiday for example – the gift that they would give differs, as does their behaviour.  Does this mean that presents given to us girls on Valentine’s Day (obligatory gift-giving) would be worse than the gifts our blokes would give us on any random day simply because they felt like it (voluntary gift-giving)?  Does it also mean that they would feel and act differently after the giving?  Are they giving us presents because they mean it, or just because they feel that they have to….?

Many men feel that it is all down to them on Valentine’s Day, for them to make the effort.  Rugimbana et al. (2003) support this by claiming that there is a social power relationship between the genders on Valentine’s Day.  These findings also back up what I mentioned earlier; that it is stereotyped that men are the ones who are supposed to do the pampering and women are the ones who are to be pampered.  These stereotypes may have occured due to the proposed social power relationship.

Whether it’s due to social pressures, simply what is expected or because they enjoy spoiling us, overall it looks as though it’s up to the fellas to do the work on the 14th February.  There is research into the topic, but personally I prefer the idea that men want to treat us well, and are being chivalrous.  Deluded, you might say, but it may be the case!  In about a week and half, regardless of your gender or relationship status, I hope you all have a happy Valentine’s Day.

 

 

References:

• Otnes, Ruth and Milbourne (1994) — http://www.acrwebsite.org/volumes/display.asp?id=7578
• Goodwin, Smith and Spiggle (1990) — http://onlinelibrary.wiley.com/doi/10.1002/cb.122/abstract
• Rugimbana et al. (2003) — http://www.acrwebsite.org/volumes/display.asp?id=7086&print=1

For my TA – comments due by friday week 11

• http://hls92.wordpress.com/2011/12/05/why-is-reliability-important/#comment-51
• http://ruthtanti.wordpress.com/2011/11/15/wk8-qualitative-research-isnt-as-scientific-as-quantitative-methods/#comment-48
• http://notwilliam.wordpress.com/2011/11/25/was-milgrams-study-into-obedience-unethical/#comment-78
• http://leylaosman.wordpress.com/2011/12/09/qualitative-or-quantitative-data/#comment-53

Ethics in research studies

In my point of view, ethics is one of the most important aspects of psychological studies.  Not only does it protect participants from physical and psychological harm, but the ethical guidelines introduced in 1973 by APA also ensures that every study has the same guidelines before they even begin, so can be compared to one another effectively.

For me, the first study that pops into my head when I hear the word ‘ethics’ has got to be Milgram’s infamous electric shock obedience study.  For those of you who haven’t heard of it, I’ll briefly explain…
Participants were sat down in a room with an apparent experimenter who was dressed in a lab coat standing next to them.  This person was in fact a confederate who was in on the whole study.  Participants saw another ‘participant’ in the room nextdoor who was hooked up to a machine which they were told gave out electric shocks at different levels of strength.  This again was actually a confederate, and the machine didn’t actually give out any shocks at all.  When the confederate who was hooked up to the machine was asked a question and answered incorrectly, the participant was told by the confederate in the lab coat to press a button that would give the electric shock which gradually increased in voltage the more questions they got wrong.  Despite hearing screams and begs to stop from the person being ‘shocked’ (they remained unseen for the rest of the experiment), it was found that the majority of participants went up to the highest shock possible which was of a clearly fatal amount, simply because they were told to. 
The ethics of this study have always been highly debated, as many of the participants became visibly highly distressed during the study.  However, it must be considered in context.  At the time, Milgram broke no ethical guidelines or bended any laws, as the guidelines which we use today were introduced 10 years later.  Milgram was in actual fact given an award for Advancement in Science 2 years after this study, so why would he have recieved this if his study was apparently so unethical?

Another aspect of ethics is that of animal experimentation.  The animals act which came into being in 1986 says that animal experimentation is only acceptable if the potential results could be important enough to justify the experimentation on animals.  For example, using animals in experiments to possibly find a cure for cancer.  It must be considered, however, that animals cannot give consent, which is a big part of ethics.  Some humans who are unable to give consent do not take part in studies, so many argue the case of ‘why should animals be any different?’  It’s a much debated topic, which I haven’t got time to go into in one little blog, so this is where I’ll stop!
Ethics is an incredibly important aspect of research.  Just think where we would be without it….