HOW RESPONSIBLE ARE YOU?
a statistical survey
Rachael Murray
INTRODUCTION
Today’s society is something of a paradoxical paradigm. We try to enforce the idea that personal responsibility is a goal that should be aspired to, yet really there are no or few models to enforce this idea. Peer relations and attitudes often try to persuade people into a world of carelessness and thoughtlessness because it’s "cool." The entertainment industry is rarely any better. Often times, the main protagonist can be seen doing anything from wadding a piece of paper and letting it drop wherever it lands to abusing their bodies by drinking to excess or doing drugs and making it seem like a socially acceptable thing to do to blow up buildings because it seemed like a good idea at the time. To actually be and act responsibly is more an act of constant struggle and perseverance, and those who choose this path are like salmon forever swimming upstream. Fighting the path of least resistance.
I wanted to know the attitudes of some of the students at Southwest Missouri State--to see what they found acceptable, and whether certain minor behaviors may lead to more major ones. For example (though not a part of my survey; this is merely an example), if someone thinks it’s okay to just pick up a couple dollars that are just lying around, are they more likely to think that it’s okay to "borrow" an object and never return it. Are they more likely to take something for the simple reason that they wanted it? Do small lapses in personal responsibility lead to bigger, more serious, or more dramatic lapses in personal responsibility, perhaps to the degree where it no longer affects just them, but possibly the people around them.
METHODS
Subjects: The participants of this survey were students from an Introduction to Psychology course (PSY 121) and were volunteers for the purposes of this project. The students had signed up on a sheet of paper and were given extra credit by their teachers for participating in the surveys. A total of 30 students filled out the questionnaire for my project.
Apparatus: My questionnaire was comprised of two main sections. The first part was used to gather certain demographic information: age, gender, class rank, etc. The second part asked a series of questions that asked about attitudes on different situations by measuring attitudes about personal level of responsibility, and responsible behavior in general.
Procedure: The volunteers were each asked to fill in several questionnaires for different students’ projects. The students who participated were told they did not have to fill them out if they did not wish to. To preserve anonymity, no student was asked or allowed to put their name or other directly identifying information (Social Security number, birth date, home address, etc.) anywhere on the questionnaires they filled out.
RESULTS
The mean age of the respondents was 21.14 with a standard deviation of 5.78. Females represented 53.33% of the respondents participating, and males represented 43.33%. This leaves 3.33% unaccounted for as there was one respondent who did not answer on gender. Of the twenty-nine who responded as to gender, 26.7% admitted to smoking, and 73.3% admitted to drinking alcohol. (The term admitted is used to account for the fact that respondents may not have answered honestly.) Twenty-three point three percent (23.3%) of those responding neither smoke nor drink, do it is evident that several of the respondents both smoke and drink alcohol.
There was a great variety of topics between the questions with Strongly Disagree, Disagree, No Opinion, Agree, and Strongly Agree questions, all trying to assess each respondents attitudes about their responsibility in general. As I would imagine is very possible with such a spread of variables, certain correlations came to light that, while high, proved to be a matter of common sense (5.61** correlation between age and rank) or sheer chance (4.18* correlation between attending class every day and feeling angry when someone carelessly disposes of a cigarette).
Most of the correlations tend to make sense, and some of them are simply interesting.
There is a high positive correlation of .540** between those who felt it was okay to litter as long as it was small and those who felt it was okay to litter at any time. There is a high negative correlation of -.484** between small litter and anger over careless disposal of spent cigarettes. There is also a relatively high negative correlation of -.467* between gender and the notion of it’s all right to drive after a few drinks "as long as I’m careful." (The negative correlation is significant in that males were described with the variable 0 and females with the variable 1. The negative correlation means that this view is more typically held by males than by females.) There is a relatively high negative correlation of -.404* between whether students admitted to skipping classes from time to time and their GPA. Also, there is a relatively high negative correlation between how closely a student attributes their attendance in a class to how well they do in that class with their impression of what kind of parents they have (-.440*) and a somewhat low, but still statistically significant, positive correlation between attendance/how well a student performs with whether they admit to skipping classes now and then (.372*).
The remaining correlations are apparently linked to each other in some fashion. The variables in question are how often a person drinks alcohol (qdrink), how often a person smokes (qsmoke), and whether a person drinks (drink) or smokes (smoke). Some of this data may sound absurdly obvious--and some of it may just sound absurd--but I feel it is noteworthy. First, there is an incredibly high negative correlation (-.951**) between smoke and qsmoke and a high negative correlation (-.686**) between drink and qdrink. There is a high positive correlation (.642**) between qsmoke and qdrink. Also, I found a high negative correlation of (-.623**) between smoke and qdrink, but interestingly a statistically insignificant correlation of -.282 between qsmoke and drink.
[Explanations and possible implications of these data will be found in the Discussion section of this project.]
BASIC RESULTS
Age: mean - 21.14
standard deviation - 5.78
Sex: male N = 14/46.67%
female N = 15/50%
[discrepancy in N due to one person not indicating gender on their survey]
How often do you smoke/drink: (note, N will exceed 30 but will not exceed 60 since some respondents both smoke and drink, but do each at a different level of frequency.)
Several times a day
N = 8(13.3%)
Once a day
N = 2(3.4%)
A few times a week
N = 13(21.7%)
Very infrequently
N = 9(15%)
Never
N = 26(43.3%)
People who smoke
N = 8(26.7%)
People who drink
N = 22(73.3%)
SD -- Strongly Disagree
D -- Disagree
NO -- No Opinion
A -- Agree
SA -- Strongly Agree
SD D NO A SA Mean
1 2 1 9 16 4.28 Attend class daily
9 12 1 5 2 2.28 Attendance doesn’t = performance
5 2 1 18 3 3.41 Skip now and then
5 11 3 10 0 2.62 Litter if it’s small
16 11 2 0 0 1.52 Litter at any time
4 8 8 5 4 2.90 Cigarette carelessness -> anger
9 3 4 13 0 2.72 Drive after drinking if "careful"
5 7 4 11 2 2.93 Speed at any time
15 8 3 2 1 1.83 Don’t wear seat belt if dressed up
1 3 9 13 3 3.48 Always have designated driver
MEANS FOR MALES AND FEMALES
MEAN SIG.LEVEL
Male Female
N = 14 N = 15
[discrepancy in N due to one person not indicating gender on their survey]
4.36 4.20 .699 Attend class daily
1.93 2.60 .161 Attendance doesn’t = performance
3.07 3.73 .174 Skip now and then
3.73 2.52 .679 Litter if it’s small
1.64 1.40 .311 Litter at any time
3.07 3.36 .481 Cigarette carelessness -> anger
3.36 2.13 .011 Drive after drinking if "careful"
2.71 3.13 .388 Speed at any time
1.86 1.80 .892 Don’t wear seat belt if dressed up
3.36 3.60 .501 Always have designated driver
Value chart:
SD = 1
D = 2
NO = 3
A = 4
SA = 5
* * * CORRELATION COEFFICIENTS * * *
AGE ANY ATTND BRTH CIG DESIG DR DRINK GENDR GPA HOW PARENT QTY QTY RANK SEAT SKIP SM SMOKE SPEED
LITTR ORDR ANGRY DRVR DRV WELL DRINK SMOKE BELT LTTR
AGE 1.000 -.235 .234 -.261 -.012 .319 -.081 .284 .219 .056 -.061 .101 .241 .189 .561** -.028 -.225 .143 -.198 .122
ANY
LITTR -.235 1.000 -.130 -.110 -.287 -.056 .279 .191 -.195 -.343 .022 -.050 -.117 .000 -.126 .045 .293 .540**.000 -.167
ATTND .234 -.130 1.000 -.132 .418* .242 -.100 -.068 -.075 .000 -.096 -.093 .059 .174 .189 -.436*-.130 -.171 -.174 -.025
BIRTH
ORDER -.261 -.110 -.132 1.000 .102 -.155 -.057 .169 -.350 -.018 -.195 .325 -.037 .048 -.128 .075 -.093 -.111 .008 -.036
CIG
ANGRY -.102 -.287 .418* .102 1.000 -.011 .028 -.174 -.136 .232 -.002 -.055 .269 .321 -.003 -.140 -.310 -.484**-.198 .148
DESIG
DRVR .319 -.056 .242 -.155 -.011 1.000 .005 -.187 .130 -.271 .034 .186 .215 .336 -.287 -.056 .150 -.032 -.415* .189
DR
DRV -.081 .279 -.100 -.057 .028 .005 1.000 .327 -.467*-.105 .075 .008 -.332 -.025 -.051 .114 .169 .332 .033 -.057
DRINK -.284 .191 -.068 .169 -.174 -.187 .327 1.000 -.061 -.056 .006 -.211 -.686**-.282-.214 .100 .139 .204 .333 -.061
GENDER .219 -.195 -.075 -.350 -.136 .130 -.467*-.061 1.000 .098 .267 -.229 -.043 -.243 .119 -.026 .260 -.080 .287 .167
GPA .056 -.343 .000 -.018 .232 -.271 -.105 -.056 .098 1.000 -.057 .044 .144 .168 .000 -.156 -.404* .103 -.053 -.164
HOW
WELL -.061 .022 -.096 -.195 -.002 .034 .075 .006 .267 -.057 1.000 -.440*-.068 .128 -.118 .169 .372*-.073 -.146 -.145
PARENTS .101 -.050 -.093 .325 -.055 .186 .008 -.211 -.229 .044 -.440* 1.000 .016 .169 -.129 -.094 -.138 .140 -.139 .164
QDRINK .241 -.117 .059 -.037 .269 .215 -.332 -.686**-.043 .144 -.068 .016 1.000 .642**.275 .045 -.341 -.238 -.623** .000
QSMOKE .189 .000 .174 .048 .321 .336 -.025 -.282 -.243 .168 .128 .169 .642**1.000 .048 .056 -.217 -.097 -.951**-.167
RANK .561**-.126 .189 -.128 -.003 -.287 -.051 -.214 .119 .000 -.118 -.129 .275 .048 1.000 -.036 -.126 -.112 -.028 -.121
SEAT
BELT -.028 .045 -.436* .075 -.140 -.056 .114 .100 -.026 -.156 .169 -.094 .045 .056 -.036 1.000 .084 -.045 -.091 .278
SKIP -.225 .293 -.130 -.093 -.310 .150 .169 .139 .260 -.404* .372* -.138 -.341 -.217 -.126 .084 1.000 .205 .133 -.201
SMLITTR .143 .540**-.171 -.111 -.484**-.032 .332 .204 -.080 .103 -.073 .140 -.238 -.097 -.112 -.045 .205 1.000 .097 -.316
SMOKE -.198 .000 -.174 .008 -.198 -.415* .033 .333 .287 -.053 -.146 -.139 -.623**-.951**-.028 -.091 .133 .097 1.000 .117
SPEED .122 -.167 -.025 -.036 .148 .189 -.057 -.061 .167 -.164 -.145 .163 .000 -.167 -.121 .278 -.201 -.316 .117 1.000
* - Correlation is significant at the 0.05 level (2-tailed)
** - Correlation is significant at the 0.01 level (2-tailed)
DISCUSSION
The correlation between those who felt it was okay to litter as long as the object was small and those who felt it was okay to litter at any time, because it is high and positive and because the variables were described from 1 (strongly disagree) to 5 (strongly agree), one could assume either that those who littered when the object was small would likely progress to littering more or that those who littered regardless of object size or location would certainly have no compunction against littering something small, possibly thinking that it is the tiniest of their littering "evils."
The correlation between small litter and anger over careless disposal of cigarettes, being high and negative, indicates that the more those who disagree with the statement of "I litter as long as the litter is small," the more likely they are to feel angry about seeing someone carelessly dispose of a cigarette. Taking this with the correlation of .321 ( somewhat high, though not quite statistically significant) between the quantity a person smokes and whether or not they become angry, you can see that the more a person smokes, the less they agree that they become angry about cigarette disposal. This could be because it is how they dispose of their own cigarettes and do not frown on their own behavior.
As stated before, the correlation (-.467*) between gender and whether they agreed that they could drive after a couple drinks as long as they were "careful" seems to show that more males agree with this statement than females. Does this mean that college males tend to party more than females or does it mean that they are more likely to drink alcohol than females, or is it that they are less responsible with their drinking than women are?
The correlation between GPA and skipping classes (-.404*) could mean one of two things. Either students disagree that they skip classes and that is reflected by a higher GPA, or students agree that they skip classes and that is reflected by a lower GPA. I’m sure this is a statistic that many teachers will like, especially after all the fuss that students put up about the policy stating that attendance cannot be a determining factor for a teacher to use when figuring their grade. This correlation would seem to show that attendance certainly is a factor whether or not teachers mark it down. Either the students show up and have a corresponding higher grade, or they do not show up and have a corresponding lower grade.
The correlation between attendance/performance and parent type (-.440*) demonstrates that the more likely a student feels that their attendance has nothing to do with how well they do in a class, the more likely they would describe their parents as controlling. Contrariwise, it shows that the more they feel their attendance does play a part in how well they do in a class, the more they would describe their parents as permissive. While this correlation is statistically significant, I find it hard to determine any other kind of significance. Perhaps being pushed hard by their parents in terms of academic performance led them to develop a negative attitude about showing up.
The correlation between attendance/performance and skipping classes, the lowest of my statistically significant findings, indicates that the more a person agrees that they skip classes now and then, the less importance they place on attendance determining how well they do in a class, which could lead back up to the permissive type of parent who would accept their child’s attitude of a poor academic work ethic.
The last set of correlations, those having to do with drink, qdrink, smoke, and qsmoke are ones that I find interesting. The very high correlation between smoke and qsmoke would seem to demonstrate the addictiveness of cigarettes, showing that those who smoke smoke a lot. The high correlation between drink and qdrink seems to show a similar result, tho not to the same degree, that of the respondents in my survey, those who drank, seemed to drink quite a bit. This could have to do with the party, binge drinking aspect of college life, but is not totally supported by the addictiveness factor. Some of those who drank did so in moderation, but almost all who smoked did so a great deal. This could show that cigarettes have a greater addictiveness value than alcohol does or that smoking is more socially acceptable than drinking. I would tend to not believe the latter since so many things now are No Smoking-oriented.
The high correlation between qsmoke and qdrink seems to indicate that those who smoke a lot drink a lot as well and vice versa. Take that idea along with the correlation between drink and qsmoke and the correlation between smoke and qdrink. The significance is between smoke and qdrink, indicating that those who smoke drink more, but those who drink don’t necessarily even smoke, much less smoke with any frequency. This could be taken to say that smoking leads to drinking but drinking doesn’t lead to smoking, but if you’ve ever been to an Alcoholics Anonymous meeting, you see a lot of people trading drinking for smoking, so you have to wonder just how true that is.
I wasn’t necessarily expecting any particular results from this study. However, I’d say that I’ve learned something about the college dynamic, though this knowledge is somewhat skewed by the fact that of the thousands of students at SMSU, only 30 responded on my survey. One thing I found interesting was that of the 30 people who responded, there were only 6 who never drank alcohol. I think that is a significant finding in itself, as it shows that the other 80% of the respondents do to one degree or another.
The biggest problem I can think of in this survey was that it was too small of a sample size. I would like to be able to reexamine the data (or at least learn the results upon reexamination of the data) with a sample size of one hundred, one thousand, and ten thousand students. It would be interesting to see just how far out this college dynamic extends, if it is the same or similar across different campuses nationwide. Hopefully it’s not. I wouldn’t like to know that 80% of college students nationwide drink alcohol to one extent or another. Even with responsible drinkers out there, I think that’s a rather scary statistic to go to bed with.