Better Sleeping Quality in a Youthful Cohort Is Associated with

Better Emotional Regulation, Reaction Speed and Short Term

Memory Skill

Ruohan Hu

Shanghai United International School Gubei Campus, Shanghai, Shanghai 201103, China

Keywords: Sleeping Quality, Emotional State, Short-Term Memory, Stimuli.

Abstract: Sleep is an essential aspect of our life. Sleeping plays a significant role in refreshing the brain, it can remove

the toxic from the brain which sustains oneself for a whole day. Tiredness, concentration problems, loss of

appetite can become direct consequences of sleeping deprivation. As a team, this work decided to investigate

into the correlation between sleep and these distinct aspects. In general, to conclude our researches, the

analysis supported the hypothesis on the positive correlation between sleeping quality and short term memory.

The correlation between sleeping quality and emotional state and reaction speed shows no significant results.

Also, this work would develop further on the correlation between depression level and reaction speed to

observe farther impact for emotion onto perceptual learning ability.

1 INTRODUCTION

Processes related to keeping circadian rhythm have

not been given a specific suggestion of how should

one maintain and evaluate its sleep cycles. Yet, there

are hypotheses explaining the purpose and the

importance of keeping a daily rhythm in sleeping.

During the progress of sleeping, rhythm can be seen

as a brain’s function to disconnect the cortex from

sensory input, thus achieving the effect of refreshing

the brain system. Distinct neurons can perform

differently when getting through REM state. A

suitable example would be acetylcholine which is a

neurotransmitter to help your brain keep information

gathered while you are awake and regulate REM

sleep. (Watson, Baghdoyan and Lydic 2010)

Researchers suggested that adequate sleep should

be defined as 6–8 hours per night regularly (Chen,

Wang, Jeng 2006). However, nowadays, more and

more experts suggested using sleeping hours to

measure how well a person sleep during the night is

not accurate. If individuals wake up at night, snore, or

have insomnia, though they sleep for eight hours or

even more, they are still in the category of “lack of

sleep”. Therefore, using sleeping quality to measure

how well a person sleeps during night is a more

precise way since this report would take issues as

urinary frequency into consideration. An example of

the sleeping quality measurement is the Pittsburgh

Sleeping Quality Index. Getting a result of 83% from

the total points in PSQI tests would be seen as good.

Getting good quality sleep is significant to

people’s health, but there is a group of individuals who

are developing a stage where they have troubles of

falling asleep. Researches conducted by Mary

Carskadon at Brown University suggested that “sleep

requirements do not decrease between adolescence

and teenagers, yet changes in circadian mechanisms

make it progressively harder for teenagers to fall

asleep early in the evening.” (Carskadon 2012) As a

result, teenagers sleeping times sometimes cannot

meet the requirements to sustain their daily activities

which means that they are facing sleeping deprivation.

The list of negative outcomes can be detrimental to

adolescents which include inattention, poor grades,

behavior problems, substance use, driving crashes,

overweight, and immune system compromise. (Xu,

and Wu 1986)

Thus, the main aim of this review is to introduce a

more detailed way of how sleeping quality can affect

adolescents’ mood and learning ability. In addition,

we describe depression index may appear a positive

relationship with reaction speed.

Better performance of sleeping quality in a

youthful cohort is associated with emotional

regulation, reaction speed and short term memory skill

in positive contexts.

Hu, R.

Better Sleeping Quality in a Youthful Cohort is Associated with Better Emotional Regulation, Reaction Speed and Short Term Memory Skill.

DOI: 10.5220/0011251500003438

In Proceedings of the 1st International Conference on Health Big Data and Intelligent Healthcare (ICHIH 2022), pages 239-244

ISBN: 978-989-758-596-8

239

2 GOAL AND HYPOTHESIS

There are three hypotheses of this research, all

hypotheses are the correlations between sleeping

quality and different aspects of living. First of all, we

hypothesize better performance of one’s sleeping

quality results in more positive emotion. Secondly,

we hypothesize better sleeping quality Amy results in

quicker reaction speed of recognition. At last, we

assume that better performance of somebody’s

sleeping quality results in better short-term memory.

By understanding the results of this study, our

goal is to persuade people to take sleep more seriously

since sleep deprivation would lead to harmful impacts

which can easily affect youngster’s mental health and

learning ability. To continue, we would like to share

our results in adolescence’s mental health research.

We received 34 participants’ answers to a combined

survey to test depression level. The mean of the

analysis is 12.26 points which is included in the

category of “mild depression” area in the marking

scheme (With the standard deviation of 6.146). The

maximum results of this survey is 24 points which

should be categorized in the “moderate depression”

area. We want to raise awareness of the mental health

issue among young adults and admonish them to take

care of their stress and release pressure.

3 METHOD

There are a total of 4 parts in our research process,

which were a sleeping quality survey, a temporary

emotional survey, a short-term memory test, and a

reaction speed test.

3.1 Participants

We choose the participants from the age set of 16-26

since we want to focus on the correlation between

sleep and mood as well as learning abilities among

youngsters. There is no reward system in this research

and we chose to use the method of “volunteering”

which is a way of proactively offering work to

participants. We expected to receive 160 pieces of

information from forty participants, but because some

of the data is incomplete, so we finally received 136

pieces of information with 34 participants. Some of

the tests were done online via the internet, and some

of the tests were done offline in person.

3.2 PSQI Test

The PSQI test is a sleeping quality test called

Pittsburgh Sleeping Quality Index. PSQI test is a test

consisting of 19 questions measuring the sleeping

quality for one month. It is developed by Pittsburgh

University and is highly reliable and valid in

assessments of sleeping diagnostics. The test includes

questions like: During the past month, how long (in

minutes) has it usually taken you to fall asleep each

night? Or Loud snoring? Long pauses between

breaths while asleep? We delivered the test to our

participants through a program and waited for their

response. Based on the performance of our

participants, the mark scheme would be poor(Testing

points=>5),the other is good(Testing points <5).

3.3 Depression Test

Questions from the depression test are chosen from a

depression survey from depression.org and

mayoclinic.org which are two credible organization

that devote them into depression career,

depression.org is supported by the New Zealand

government. The depression test consist of 20

questions that are evaluated with the marks of 0-3

points in each question while 3 points represented

every time, 2 points represented most of the time, 1

point represented some of the time(or rarely) and 0

means never. An example would be: How often have

you been bothered by thoughts that you would be

better off dead, or of hurting yourself in some

way over the last two weeks? Rate from 0-3. The

marking scheme would be Depression Severity: 0-10

none, 11-21 mild, 22-32 moderate, 33-43 moderately

severe, 44-60severe.

3.4 Memory Test

According to the Wechsler Memory Scale published

in 2009, a neuropsychological test that is used to

assess one’s general cognitive screener, logical

memory, visual memory, we constructed a simplified

test a simplified test to mitigate our environmental

difficulty. The test includes three sections:

association learning, random number quick recalling,

and face-associated feature recognition

(Vandekerckhove, Wang 2017).

In the first part of the quiz, a total of 18 pairs of

Chinese phrases were displayed to the participants,

half of the phrases were related to each other and half

were not. (eg. Pants-shirts and faith-exaggeration)

Participants were given 20 seconds to memorize the

words and to write down the exact combination of the

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word pair. There are two trails in total.

For the second part of the test, participants were

required to memorize random number sequences for

the given 1.5 seconds and to write them down within

3seconds. There are eight sequences with 7 numbers,

one sequence with 5 numbers, one sequence with 6

numbers, one sequence with 8 numbers and one

sequence with 9 numbers. (eg. 3860213)

For the final task in this test, participants needed

to remember three lines of information in 15 seconds

with connected faces. There were three faces in one

slide matching with 3 detailed information for each

face. The information included nationality, job and

age. Four rounds of trails were conducted, including

western male trail, asian male trail, western female

trail and asian female trail.

The marking scheme for the memory test are the

following. First section: 3 scores for one correct

meaningful set, 6 scores for the correct memorization

of meaningless sets. Second section: 1 score for the

sequence with 5 numbers, 2 scores for the sequence

with 6 numbers, 3 scores for sequences with 7

numbers, 4 scores for the sequence with 8 numbers, 5

scores for the sequence with 9 numbers.Third section:

1 score for one correct feature associated with the

matching Eastern face, 2 scores for one correct

feature associated with the matching Western faces.

The test consist of 252 scores in total, participants

getting scores higher than 110 would be considered

performing well, while those ending up 110 scores or

less would be judged as poor.

3.5 Reaction Test

The reaction test examines the reaction speed of the

contestants. The participants were asked to find out

requested numbers or Chinese characters in lists of

numbers. (eg. Find 6 in 23578495628985687, the real

questions are more complicated) There were

questions relating to shapes as well. The whole test

consists of 11 questions, the researchers didn’t need

to calculate the exact points but to measure the time

for participants to complete. If the participants exceed

160 seconds, they would be seen as poor; if the

participants’ calculated time is below 160 seconds,

they would be seen as good.

4 RESULTS ANALYSIS

We did Pearson Correlation test, obtaining p value

and r value. We also completed regression test and t

test.

4.1 Pearson Correlation Analysis

According to the Table 1, correlation is significant

when the p value is < 0.05. Since the correlation

between sleeping quality and depression is p=0.445,

and the correlation between sleeping quality and

reaction time is p=0.863, unfortunately, we found no

significant correlation between sleeping quality and

depression, sleeping quality and reaction speed.

The P value for sleeping quality and memorizing

index is 0.029, so they are related. The R value

indicates whether two variables are positively or

negatively related. The range of R value is between -1

to +1. The R value between sleeping quality and

memorizing index is 0.374 which means that higher

the sleeping quality results in higher short-memory

skill.

Table 1: Pearson test correlation.

Better Sleeping Quality in a Youthful Cohort is Associated with Better Emotional Regulation, Reaction Speed and Short Term Memory Skill

241

4.2 Regression Test

After determine the positive relationship between

sleeping quality and memorizing index. The R Square

value continues indicates the correlation which

sleeping quality would have contribution to at least

14% of the memory index score. This is a dominate

factor.

Table 2: Regression Test of three variables.

The histogram of regression residual and the

linear P-P plot of regression standardized residual

both indicates that the residuals are in a trend of

normally distribution. Therefore, the variables did not

appeared bizarre results, and it contributes to the

conclusion since the variables were not abnormally

affecting the hypothesis.

(a) (b)

Figure 1: P-P plot of memorizing index.

4.3 T-test

In this test, we divided the participants into two

groups based on their results in sleeping quality tests.

The two groups are poor (=>5),the other is good(<5).

We found out an implicit positive relationship

between sleeping quality and memory index.

Figure 2: Bar chart of good/poor sleep division.

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5 CONCLUSIONS

We created three experiments to discover the

relationship between sleeping quality and three

different aspects, we conclude: there is positive

relationship between sleeping quality and short term

memory.

We found no significant relationship between

sleeping quality and emotion where the p value

between them is 0.445, also the results shows there is

especially weak relationship between sleep and

reaction speed and the results is .886. This disproves

our hypothesis. Meaning that better sleeping quality

may not results in better emotion control and quicker

reaction speed.

There could be possible reasons why we didn’t get

to our hypothesis that will be discussed in the

following limitation section.

The P value shows correlation between memory

test and sleeping quality is 0.029 which is below 0.05,

means that there is relationships between sleep and

memory. The results is successfully. Chi-square test

divides the participants’ sleeping quality into groups

which are poor and good: the results shows for most

participants: sleeping quality has a positive

relationship with short term memory.

6 LIMITATION

There are plenty of limitations in these experiments

that lead us to the unsatisfied conclusion.

According to a study constructed by Marie

Vandekerckhove, deprivation a common symptom of

and risk factor for a range of psychiatric disorders

including anxiety and mood disorders.

(Vandekerckhove, Wang 2017) This evidence

supported our hypothesis on sleeping quality would

positively relate to emotional state. However, there

are mainly two reasons why we didn’t get to a

successful conclusion. The age group of this

experiment is restricted between 16 to 26 years old.

Human beings at this age are going through a tough

time in life which they have to be pressured by school

works and facing troubles in their adolescences as

well. A lot of participants may have feelings of

depression because of other environmental factors

rather solely by their sleeping quality. This variable

may affect the results. In addition, the participants

volunteered to be tested on the depression tests so

there may appear biases. The participants knew that

they were tested by the researchers, so they would

answer the question as they imagine to be beneficial

to the researches. Therefore, participation bias is

created, it may varies the results.

There may appear two limitations in the reaction

speed test. First, some of the participants finished

their tests via internet. There could be problems

during the tests, for instance internet lagging,

communication problems etc. Thus, the time record

could be different than whom finished the test offline,

this could affect the results. Lastly, the reason why

there appears no significant relationship, could

because of the average quality of the participants are

too high. Therefore, whatever the sleeping quality

results they get can lead to a high score in reaction

speed tests.

The emotional test and the reaction speed test are

not successful, so we would like to redo these two

tests in a modified notion. We would proceed this

experiment offline collecting information from a

more diversified age group. The ideal age group is

from age 16 to age 50, this could create a more

pluralistic atmosphere and hopefully reduce

variables. We are not looking for older age groups

since there will be a lot of factors affecting the results,

like diseases and psychosis.

Based on the correlation graph, the p values

between depression index and reaction speed is 0.045

which is slightly below 0.05, this could be seen as

slightly significant. Thus, we would like to develop

another research investigate on the correlation

between depression level and reaction speed

specifically. As Chai M. Tyng and his team

concluded, emotional state can impact on learning

and memory, we would conduct an experiment

mainly focus on reaction speed and conclude a more

delicate result.

Table 3: P-P plot (Tyng, Amin, Saad, Malik 2017).

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REFERENCES

Carskadon M.A,. (2012) Sleep in Adolescents: The Perfect

Storm Pediatr Clin North Am. 2011 Jun; 58(3): 637–

647. doi: 10.1016/j.pcl.2011.03.003

Chen M.Y., Wang E. K., Jeng Y.J,.(2006) Adequate sleep

among adolescents is positively associated with health

status and health-related behaviors doi: 10.1186/1471-

2458-6-59

Tyng C.M., Amin H.U., Saad M.N.M, Malik A.S.(2017)

The Influences of Emotion on Learning and Memory

doi: 10.3389/fpsyg.2017.01454

Vandekerckhove M, Wang Y,L.(2017) Emotion, emotion

regulation and sleep: An intimate relationship AIMS

Neurosci. 2018; 5(1): 1–17.

doi: 10.3934/Neuroscience.2018.1.1

Watson C.J., Baghdoyan H, A. , and Lydic, R,.(2010)

Neuropharmacology of Sleep and Wakefulness Sleep

Med Clin. 2010 Dec; 5(4): 513–528.

doi: 10.1016/j.jsmc.2010.08.003

Xu, Shulian, and Zhenyun Wu. “The Construction of ‘The

Clinical Memory Test.’” Acta Psychologica Sinica,

1986.

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