Stephanie Espinal


UX Researcher & Designer

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About


I'm a huge people-person. I like helping others and making a difference in their lives. Therefore, I love Psychology and everything that comes with it. There is nothing greater than finding ways to improve people’s interaction with the world. As a UX designer, I have the opportunity to do this and more.

When I’m not in school or working, I like to read personal development books and write about them. I enjoy spending time with my family and love ones when I have the chance. I love meeting new people, learning new things and traveling the world when I can.

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The Stroop Effect


About

The purpose of this study was to examine the effects of incongruent labels on response time. It was measured through a visual processing task with 2 different condition sheets, 1 with incongruent labels (INL) and the other one with no labels (NL) both of the sheets had 40 animal silhouette ( cats, dogs, cows, pigs and bears). The 25 participants, colleges students from the University of Massachusetts Amherst, were asked to say the names of the animals aloud as soon as they could, one sheet at a time. We hypothesized that most of the participants would take less time doing the unlabeled animal silhouettes than the one with incongruent labels. The results supported the hypothesis that incongruent labels interfere with the brain’s ability to process i ages that are commonly easy to distinguish.

Process

Participants

The subjects were 25 students, 7 males and 18 females from the University of Massachusetts Amherst (UMass) between the ages of 18-23 years old (mean age: 20.08 and median age: 20.00). From all of the students only 3 were left-handed. For most of the students English was there first language except for 2 students, one spoke Spanish and the other one Portuguese. The birth order between the students were 1,2 and 3. These students were from Psych241- SEC01.

Material

We used two different sheets that had silhouettes of animals, one with no labels (figure 1) and the other one with incongruent labels (figure 2) . There were five animals in the sheets, cats, dogs, pigs, bears, and cows. Researchers had a separate sheet to record the answers, how long it took the participant to identify the animals and the number of incorrect responses. Also, on this same sheet, the researcher had to gather some demographics-background/ personal information about the participant (age, gender, birth order, first language, and handedness).

Project 1 Figure 1

Figure 1

Project 1 Figure 2

Figure 2

Procedure

This was a variation of the Stroop experiment, which had a repeated measure design and it counterbalanced each other so every student could be the researcher and subject. The experiment took place at Machmer Hall room W22, UMass Amherst. First, the researcher gave the participant the directions to read. While the participant was reading, the researcher decided whether to give the participant the sheet with or without labels depending on their condition: INC or NL. The researcher set up the timer and let the participant begin. As the participant identified silhouettes verbally left to right and top to bottom, the researcher kept track of how many non-self- corrected errors were made, but if the participant self- corrected themselves it did not count as an error. The participant had to say finished when they were done so the researcher could stop the timer. Researchers recorded everything.

Result

Overall, we concluded with strong evidence that support the hypothesis. The INL took a longer time (M =28.02, SD= .788 than the NL (M = 35.68, SD = 1.77). There was significant effect t(24) = 6.954, p< 001, d= 1.391, which supports the hypothesis that the INL would take a longer time to identify the name of the animals. The effect size of the label condition on the time to identify the animal silhouettes is larger ( d= 2.39) because it’s greater than 0.08.

Paired Samples Test
Mean Standard Deviation Standard Error Mean 95% Confidence Interval of the Difference
LowerUpper
Pair
1
TINC.
TNL
7.660
40
5.50762 1.10152 5.38896 9.93384
Paired Samples Test
t df Sig. [2-tailed]
Pair 1 TINC - TNL 6.954 24 .000

Discussion

As the hypothesis predicted, participants responded quicker to the unlabeled animal silhouettes than they did with the incongruent labeled animal silhouettes. The results agree with the earlier research done by Ehri (1975) and Stroop (1935). However, there could be factors that might affect the results in this study such as the different type of participant’s learning (eg. learning disability). Another reason could be that for some of the participants English was not their first language. Also, human error, researchers might not have started the timer at the same exact time. In the future, the Stroop effect should be studied in more people from different ages to see the difference between ages. Future studies should do the same experiment, but with young children to see if the Stroop effect starts when your young or when you get older.

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Attitudes Toward the Illegal Use of Stimulants in College


Abstract

The purpose of this study was to see the attitudes toward the use of prescription drugs such as stimulants for studying or improvements of academic performance. The participants involved in this study were 126 college students from the University of Massachusetts Amherst. The participants were approached in random places on Umass Amherst campus and asked to complete a survey. We had three hypotheses Hypothesis one was that males would be more prostimulant than females. Second, we hypothesized that students with no prescription for a stimulant, but still used a stimulant, would be pro-stimulant use. Thirdly, we hypothesized that students with higher GPAs would be more anti-stimulant use than students with low GPAs. Hypotheses two and three were supported to be true by the results. However, hypothesis one was not. We concluded that there is not significant difference between gender’s attitudes toward the use of stimulants.

Method

Participants

The subjects involved in this study were college students from the University of Massachusetts Amherst. The students that participated were only on-campus students and they were selected randomly. All the participants were recruited from all around campus at Umass Amherst. There were 126 participants in total including: 50 females, 74 males, 1 other, and 1 person who choose not to report s/he gender.

Materials

In this study we used a survey form. Participants were informed of their rights as subjects and their ensured anonymity. They were also informed they had the right to stop at any time and that they were allowed to skip any questions. The attitude scale (likest scale) used was 1-5, strongly disagree, disagree, neutral, agree, and strongly agree. The survey had 23 attitude items (questions) and the responses bias were controlled by reverse scoring. The types of demographic information requested included the gender, age, on/off campus, academic year, GPA, extracurricular activities, college they are a part of, are you prescribed a stimulant, if no, do you use one, times a week do you use a stimulant, drinks peer week, if they use marijuana, if yes, how often. One of the demographic questions related to a hypothesis was about student’s GPA. For instance we asked “What is your GPA?” and possible answers were between to <2.0 and 4.0 GPA.

Project 2 Survey
Procedure

All the researchers were students from Umass Amherst and they were part 0f Psych 241 course, there were 21 students in total. Each student administered 6 surveys, 126 in total. The ATTITUDE TOWARD ILIGAL USE OF STIMULANTS  6 participants were approached in random places around Umass Amherst campus. Surveys were anonymous, participants were never asked to put their names down, only demographics information. All the surveys were hidden ( i.e. participants gave their survey back with the demographic side up and the researchers kept them in an opaque container)

Scoring and Reliability

We needed to reverse the scale to prevent a “lazy” response pattern and response bias. The ones that were reversed were 2, 7, 10, 14, 15, 18, 20, 21. The high score for pro-stimulant use 115 and the low score was anti-stimulant total min of possible use 23. The max mean score was 5 and the min mean score was 23. The total average of is the mean of all participant’s scores. In the two cases, the attitudes indicate that the high scores means pro-stimulant users while the low scores indicate those who are more anti-stimulant . The correlation of each participant’s score on each item with that participant’s total score was 0.930. The criterion level for the correlation was 0.7 and if was less than that value, we would have had to delete some items to increase reliability. None of the items failed to meet criterion the Cronbach’s alpha was greater than 0.7.

Results

Descriptive Statistics

The mean, median and standard deviation for total score were 65.166 for the mean, 63.500 for the median, and a standard deviation of 16.970. The mean, median and standard deviation for total average were 2.842 for the mean, 2.782 for the median and a standard deviation of 0.741. The results were positively skewed, which it means that more people leaning a pro-stimulant attitude.

Inferential Statistics

The dependent variable for this study was the mean attitude score, which we measured using an attitude survey. One way ANOVA and an independent t-test was used to analyze the demographics of the participants. The independent T-test was used for whether or not students had taken the stimulant without it being prescribed to them. On the other hand, the one way ANOVA test was used to determine the difference in attitudes on the use of stimulants between females and males and other. After assessing the validity of hypothesis 1, which stated that males are significantly more pro-stimulant use than females, we found that there is no statistically significant correlation between gender and attitudes toward stimulants use F(2 , 122) = 1.281, p = .281. The mean for males was 2.961 with a standard deviation of 0.734 while females have the mean of 2.792 with standard deviation of 0.728. For hypothesis 2, which stated that students taking stimulants with no prescription have more pro-attitudes towards stimulant use, a statistically significant difference was found, t(124) = 8.87, p < .001. Students without prescription, but would still take stimulants had a mean of 3.874 with a standard deviation of 0.603. While the students without prescription, but wouldn’t take stimulants had the mean of 2.626 with a standard deviation of 0.570. After testing hypothesis 3, which stated that students with higher GPAs would be more anti-stimulant use than students with low GPAs, a statistically significant correlation was found between GPA sand attitudes toward stimulants use F(2 , 121) = 4.294, p = .006. We used Tukey’s Post-hoc tests for hypothesis 3. Tukey’s Post-hoc test indicated this difference lay between students of GPAs from 2.5-3.0 and students of GPA from 3.5-4.0 such that the former had more pro-stimulant use attitudes, and the latter less. Using a significant ANOVA test we ATTITUDE TOWARD ILIGAL USE OF STIMULANTS  8 found that p= .003 between GPAs from 2.0- 2.5, 2.5-3.0 and 3.5-4.0. Moreover, the mean for students with a 2.0-2.5 GPAs was 2.811 with a standard deviation of 0.153, for students with a GPAs between 2.5-3.0, their mean was 3.267 with a standard deviation of 0.755. The students with GPAs between 3.0-3.5 had a of mean 2.856 with a standard deviation of 0.713. Lastly, the students with GPAs between 3.5-4.0 had a mean of 2.834 with a standard deviation of 0.701.

Discussion

The results found that Students lean towards a pro-stimulant attitude. Students don't mind using drugs or having friends that use them just for recreational use. The criterion level for the correlation was 0.7 and if it was less than that value, we didn’t have to delete items to increase reliability. None of the items failed to meet the criteria. The Cronbach’s alpha was greater than 0.7. The survey was considered reliable because no matter how many times researchers use it, it would have the similar results (consistency). The survey was valid to measure of what we intended to measure, which it was the independent variable for this study, the mean attitude score. As the hypotheses predicted, hypothesis two, that students with no prescription for a stimulant, but still used a stimulant, would be pro-stimulant use and hypothesis 3, that students with higher GPAs would be more anti-stimulant use than students with low GPAs, were supported. However, hypothesis one, that males would be more pro-stimulant than females, was not supported. This is because a non-significant correlation was found, males were not significantly more pro-attitude than females. In this case, we didn’t have the same results that Fejer (1973) found in her study, which was that males knew more than females about drugs and had a more permissive attitude towards them. Limitations of this study were the fact that the sample of participants was rather small and it might not be a good representation of all college students. Fejer (1973) conducted a survey among 4693, which is a lot of students. Also, this study was conducted only at Umass Amherst and it might not represent all the college students from other universities. Future studies on the same topic could use a survey form, but with specific or different age ranges for example, people between 18-28 or 35-45 and see what their feelings are towards the recreational use of drugs. Do they feel the same way? or do they feel different? Another future study would be to see under what circumstances people are more likely to use recreational stimulants (e.g. stress, anxiety, depression)

Appendix

Table 1 Table 2 Table 3 Table 4 Table 5 Table 6 Table 7 Table 8 Table 9
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Lorem ipsum dolor sit amet, consectetur adipisicing elit. Mollitia neque assumenda ipsam nihil, molestias magnam, recusandae quos quis inventore quisquam velit asperiores, vitae? Reprehenderit soluta, eos quod consequuntur itaque. Nam.

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Lorem ipsum dolor sit amet, consectetur adipisicing elit. Mollitia neque assumenda ipsam nihil, molestias magnam, recusandae quos quis inventore quisquam velit asperiores, vitae? Reprehenderit soluta, eos quod consequuntur itaque. Nam.

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